notes on research methodology for MBA II

UNIT I

Q.1. What do you mean by research? Explain its objectives, significance and types?

Ans. Research in simple terms refers to search for knowledge. It is a scientific and systematic search for information on a particular topic or issue. It is also known as the art of scientific investigation.

According to Redman and Mory (1923), research is a “systematized effort to gain new knowledge”. It is an academic activity and therefore the term should be used in a technical sense. According to Clifford Woody, research comprises “defining and redefining problems, formulating hypotheses or suggested solutions; collecting, organizing and evaluating data; making deductions and reaching conclusions; and finally, carefully testing the conclusions to determine whether they fit the formulated hypotheses”.

Thus, research is an original addition to the available knowledge, which contributes to its further advancement. It is an attempt to pursue truth through the methods of study, observation, comparison and experiment. In sum, research is the search for knowledge, using objective and systematic methods to find solution to a problem.

Objectives of Research:

The objective of research is to find answers to the questions by applying scientific procedures. In other words, the main aim of research is to find out the truth which is hidden and has not yet been discovered. Although every research study has its own specific objectives, the research objectives may be broadly grouped as follows:

1. To gain familiarity with new insights into a phenomenon (i.e., formulative research studies);

2. To accurately portray the characteristics of a particular individual, group, or a situation (i.e., descriptive research studies);

3. To analyse the frequency with which something occurs (i.e., diagnostic research studies); and

  4. To examine the hypothesis of a causal relationship between two variables (i.e.,    hypothesis-testing research studies).

Significance of Research:

According to a famous Hudson Maxim, “All progress is born of inquiry. Doubt is often better than overconfidence, for it leads to inquiry, and inquiry leads to invention”. It brings out the significance of research, increased amount of which makes the progress possible. Research encourages scientific and inductive thinking, besides promoting the development of logical habits of thinking and organisation. The role of research in applied economics in the context of an economy or business is greatly increasing in modern times. The increasingly complex nature of government and business has raised the use of research in solving operational problems. Research assumes significant role in the formulation of economic policy for both, the government and business. It provides the basis for almost all government policies of an economic system. Government budget formulation, for example, depends particularly on the analysis of needs and desires of people, and the availability of revenues, which requires research. Research helps to formulate alternative policies, in addition to examining the consequences of these alternatives. Thus, research also facilitates the decision-making of policy-makers, although in it is not a part of research. In the process, research also helps in the proper allocation of a country’s scarce resources.

Research is also necessary for collecting information on the social and economic structure of an economy to understand the process of change occurring in the country. Collection of statistical information, though not a routine task, involves various research problems. Therefore, large staff of research technicians or experts is engaged by the government these days to undertake this work.

Research also assumes significance in solving various operational and planning problems associated with business and industry. In several ways, operations research, market research and motivational research are vital and their results assist in taking business decisions. Market research refers to the investigation of the structure and development of a market for the formulation of efficient policies relating to purchases, production and sales. Operational research relates to the application of logical, mathematical, and analytical techniques to find solution to business problems, such as cost minimization or profit maximization, or the optimization problems. Motivational research helps to determine why people behave in the manner they do with respect to market characteristics. More specifically, it is concerned with the analysis of the motivations underlying consumer behaviour. All these researches are very useful for business and industry, and are responsible for business decision-making.

Research is equally important to social scientists for analyzing the social relationships and seeking explanations to various social problems. It gives intellectual satisfaction of knowing things for the sake of knowledge. It also possesses the practical utility for the social scientist to gain knowledge so as to be able to do something better or in a more efficient manner. The research in social sciences is concerned with both knowledge for its own sake, and knowledge for what it can contribute to solve practical problems.

Types of Research:

1. Descriptive Versus Analytical:

Descriptive research consists of surveys and fact-finding enquiries of different types. The main objective of descriptive research is describing the state of affairs as it prevails at the time of study. The term ‘ex post facto research’ is quite often used for descriptive research studies in social sciences and business research. The most distinguishing feature of this method is that the researcher has no control over the variables here. He/she has to only report what is happening or what has happened. Majority of the ex post facto research projects are used for descriptive studies in which the researcher attempts to examine phenomena, such as the consumers’ preferences, frequency of purchases, shopping, etc. Despite the inability of the researchers to control the variables, ex post facto studies may also comprise attempts by them to discover the causes of the selected problem. The methods of research adopted in conducting descriptive research are survey methods of all kinds, including correlational and comparative methods. Meanwhile in the Analytical research, the researcher has to use the already available facts or information, and analyse them to make a critical evaluation of the subject.

2. Applied Versus Fundamental:

Research can also be applied or fundamental in nature. An attempt to find a solution to an immediate problem encountered by a firm, an industry, a business organisation, or the society is known as applied research. Researchers engaged in such researches aim at drawing certain conclusions confronting a concrete social or business problem.

On the other hand, fundamental research mainly concerns generalizations and formulation of a theory. In other words, “Gathering knowledge for knowledge’s sake is termed ‘pure’ or ‘basic’ research”. Researches relating to pure mathematics or concerning some natural phenomenon are instances of Fundamental Research. Likewise, studies focusing on human behaviour also fall under the category of fundamental research.

Thus, while the principal objective of applied research is to find a solution to some pressing practical problem, the objective of basic research is to find information with a broad base of application and add to the already existing organized body of scientific knowledge.

3. Quantitative Versus Qualitative:

Quantitative research relates to aspects that can be quantified or can be expressed in terms of quantity. It involves the measurement of quantity or amount. Various available statistical and econometric methods are adopted for analysis in such research which includes correlation, regressions and time series analysis etc,

On the other hand, Qualitative research is concerned with qualitative phenomena, or more specifically, the aspects related to or involving quality or kind. For example, an important type of qualitative research is ‘Motivation Research’, which investigates into the reasons for certain human behaviour. The main aim of this type of research is discovering the underlying motives and desires of human beings by using in-depth interviews. The other techniques employed in such research are story completion tests, sentence completion tests, word association tests, and other similar projective methods. Qualitative research is particularly significant in the context of behavioural sciences, which aim at discovering the underlying motives of human behaviour. Such research helps to analyse the various factors that motivate human beings to behave in a certain manner, besides contributing to an understanding of what makes individuals like or dislike a particular thing. However, it is worth noting that conducting qualitative research in practice is considerably a difficult task. Hence, while undertaking such research, seeking guidance from experienced expert researchers is important.

4. Conceptual Versus Empirical:

The research related to some abstract idea or theory is known as Conceptual Research. Generally, philosophers and thinkers use it for developing new concepts or for reinterpreting the existing ones. Empirical Research, on the other hand, exclusively relies on the observation or experience with hardly any regard for theory and system. Such research is data based, which often comes up with conclusions that can be verified through experiments or observation. Empirical research is also known as experimental type of research, in which it is important to first collect the facts and their sources, and actively take steps to stimulate the production of desired information. In this type of research, the researcher first formulates a working hypothesis, and then gathers sufficient facts to prove or disprove the stated hypothesis. He/she formulates the experimental design, which according to him/her would manipulate the variables, so as to obtain the desired information. This type of research is thus characterized by the researcher’s control over the variables under study. In simple term, empirical research is most appropriate when an attempt is made to prove that certain variables influence the other variables in some way. Therefore, the results obtained by using the experimental or empirical studies are considered to be the most powerful evidences for a given hypothesis.

5. Other Types of Research:

The remaining types of research are variations of one or more of the afore-mentioned type of research. They vary in terms of the purpose of research, or the time required to complete it, or may be based on some other similar factor. On the basis of time, research may either be in the nature of one-time or longitudinal time series research. While the research is restricted to a single time-period in the former case, it is conducted over several time-periods in the latter case. Depending upon the environment in which the research is to be conducted, it can also be laboratory research or field-setting research, or simulation research, besides being diagnostic or clinical in nature. Under such research, in-depth approaches or case study method may be employed to analyse the basic causal relations. These studies usually undertake a detailed in-depth analysis of the causes of certain events of interest, and use very small samples and sharp data collection methods. The research may also be explanatory in nature. Formalized research studies consist of substantial structure and specific hypotheses to be verified. As regards to historical research, sources like historical documents, remains, etc. Are utilized to study past events or ideas. It also includes philosophy of persons and groups of the past or any remote point of time.

Research has also been classified into decision-oriented and conclusion-oriented categories. The decision-oriented research is always carried out as per the need of a decision maker and hence, the researcher has no freedom to conduct the research according to his/her own desires. On the other hand, in the case of Conclusion-oriented research, the researcher is free to choose the problem, redesign the enquiry as it progresses and even change conceptualization as he/she wishes to. Operations research is a kind of decision-oriented research, where in scientific method is used in providing the departments, a quantitative basis for decision-making with respect to the activities under their purview.

Q.2. What could be the objective of conducting research? Also discuss the qualities of a good researcher?

Ans. The importance of knowing how to conduct research is listed below:

i. The knowledge of research methodology provides training to new researchers and enables them to do research properly. It helps them to develop disciplined thinking or a ‘bent of mind’ to objectively observe the field;

ii. The knowledge of doing research inculcates the ability to evaluate and utilize the research findings with confidence;

iii. The knowledge of research methodology equips the researcher with the tools that help him/her to make the observations objectively; and

iv. The knowledge of methodology helps the research consumers to evaluate research and make rational decisions.

Qualities of a Researcher:

It is important for a researcher to possess certain qualities to conduct research. First and foremost, he being a scientist should be firmly committed to the ‘articles of faith’ of the scientific methods of research. This implies that a researcher should be a social science person in the truest sense. A researcher should possess the following qualities:

(1) First of all, the nature of a researcher must be of the temperament that vibrates in unison with the theme which he is searching. Hence, the seeker of knowledge must be truthful with truthfulness of nature, which is much more important, much more exacting than what is sometimes known as truthfulness. The truthfulness relates to the desire for accuracy of observation and precision of statement. Ensuring facts is the principle rule of science, which is not an easy matter. The difficulty may arise due to untrained eye, which fails to see anything beyond what it has the power of seeing and sometimes even less than that. This may also be due to the lack of discipline in the method of science. An unscientific individual often remains satisfied with the expressions like approximately, almost, or nearly, which is never what nature is. A real research cannot see two things which differ, however minutely, as the same.

(2) A researcher must possess an alert mind. Nature is constantly changing and revealing itself through various ways. A scientific researcher must be keen and watchful to notice such changes, no matter how small or insignificant they may appear. Such receptivity has to be cultivated slowly and patiently over time by the researcher through practice. An individual who is ignorant or not alert and receptive during his research will not make a good researcher. He will fail as a good researcher if he has no keen eyes or mind to observe the unusual changes behind the routine. Research demands a systematic immersion into the subject matter by the researcher grasp even the slightest hint that may culminate into significant research problems.

(3) Scientific enquiry is pre-eminently an intellectual effort. It requires the moral quality of courage, which reflects the courage of a steadfast endurance. The process of conducting research is not an easy task. There are occasions when a research scientist might feel defeated or completely lost. This is the stage when a researcher would need immense courage and the sense of conviction. The researcher must learn the art of enduring intellectual hardships.

In order to cultivate the afore-mentioned three qualities of a researcher, a fourth one may be added. This is the quality of making statements cautiously. A researcher should cultivate the habit of reserving judgment when the required data are insufficient.

Q.3. Describe the research process in detail? Also discuss the problems encountered by researchers in India?

Ans. Research Process:

Research process consists of a series of steps or actions required for effectively conducting research. The following are the steps that provide useful procedural guidelines regarding the conduct of research:

(1)               Formulating the research problem: The research process begins with problem discovery, and identifying the problem is the first step toward its solution. The word problem, in general usage, suggests something has gone wrong. Actually, the research task may be to clarify a problem, to evaluate a program, or to define an opportunity, and problem discovery and definition will be used in this broader context. It should be noted that the initial stage is problem discovery, rather than definition. Thus the problem statement is often made only in general terms.

The adage “a problem well defined is a problem half solved” is worth remembering. This adage emphasizes that an orderly definition of the research problem gives a sense of direction to the investigation. Careful attention to problem definition allows the researcher to set the proper research objectives. If the purpose of the research is clear, the chances of collecting the necessary and relevant information-without collecting surplus information-will be much greater.

(2) Extensive literature survey: Once the problem is formulated, the next step is to write down a brief summary of previous research so that the researcher may be familiar with what is already known and with what is still unknown and untested. This helps to eliminate the replication of work and provides useful basis for the formulation of hypothesis.

(3) Developing hypothesis: A hypothesis is a tentative explanation for certain behaviours, phenomena, or events that have occurred or will occur. A hypothesis states the researcher’s expectations concerning the relationship between the variables in the research problem; a hypothesis is the most specific statement of the problem. The hypothesis is formulated following the review of related literature and prior to the execution of the study. It logically follows the review since it is based on the implications of previous research. The related literature leads one to expect a certain relationship.

(4) Preparing the research design: After the researcher has formulated the research problem, the research design must be developed. A research design is a master plan specifying the methods and procedures for collecting and analysing the needed information. It is a framework of the research plan of action. The objectives of the study determined during the early stages of the research are included in the design to ensure that the information collected is appropriate for solving the problem. The research investigator must also determine the sources of information, the design technique (survey or experiment, for example), the sampling methodology, and the schedule and cost of the research. Once an appropriate design has been determined, the researcher moves on to the next stage-planning the sample to be used.  

(5) Determining sample design: Although the sampling plan is included in the research design, the actual sampling is a separate stage of the research process. However, for convenience, the sample planning and sample generation processes are treated together in this section. Sampling involves any procedure that uses a small number of items or that uses parts of the population to make a conclusion regarding the whole population. In other words, a sample is a subset from a larger population. If certain statistical procedures are followed, it is unnecessary to select every item in a population because the results of a good sample should have the same characteristics as the population as a whole.

(6) Collecting data: Once the research design (including the sampling plan) has been formalized, the process of gathering information from respondents may begin. When the survey method is utilized, some form of direct participation by the respondent is necessary during the process. The respondent may participate by filling out a questionnaire or by interacting with an interviewer. However the data are collected, it is important to minimize errors in the data collection process.  

(7) Execution of the project: The researcher should see that the project is executed in a systematic manner and in time. The basic aim in this stage is that the data is collected in the correct form and within the specified schedules.

(8) Analysis of data: (a) Editing and coding- Once the field work has been completed, the data must be converted into a format that will answer the decision maker’s questions. Data processing generally begins with the editing and coding of the data. Editing involves checking the data collection forms for omissions, legibility, and consistency in classification. The editing process corrects problems like interviewer errors (e.g., an answer recorded on the wrong portion of a questionnaire) before the data are transferred to a computer or readied for tabulation.

Before data can be tabulated, meaningful categories and character symbols must be established for groups of responses. The rules for interpreting categorizing, recording and transferring the data to the data storage media are called codes. This coding process facilitates computer or hand tabulation. Of course, if computer analysis is to be utilized the data are entered into the computer and verified. Computer-assisted (on-line) interviewing illustrates the impact of technological changes on the research process. Telephone interviewers are seated at a computer terminal. Survey questions are printed out on the screen. The interviewer asks the questions and then types the respondents’ answers on the keyboard. Thus answers are collected and processed into the computer at the same time, eliminating intermediate steps where errors could creep in.

(b) Analysis- Analysis is the application of logic to understand and interpret the data that have been collected about a subject. In simple description, analysis may involve determining consistent patterns and summarizing the appropriate details revealed in the investigation. The appropriate analytical technique for data analysis will be determined by management’s information requirements, the characteristics of the research design, and the nature of the data collected. Statistical analysis may range from portraying a simple frequency distribution to very complex multivariate analysis such as multiple regressions.  

(9) Hypothesis testing: After analysing the data, the researcher is in a position to test the hypothesis, if any, he had formulated earlier. It will result in either accepting the hypothesis or in rejecting it.

(10) Generalization and interpretation: Data interpretation is done with the intention of seeking explanation for the research results on the basis of existing theories and doors are thrown open for newer explanations and possibilities for further research.

(11) Preparation of the report or presentation of the results: The research report should communicate the research findings effectively. All too often the report is a complicated statement of the study’s technical aspects and sophisticated research methods. Often, management is not interested in detailed reporting of the research design and statistical findings but wishes only a summary of the findings. It cannot be overemphasized that if the findings of the research remain unread on the manager’s desk, the study is useless. The manager’s information needs will determine how much detail is provided in the written report. The written report serves another purpose: it is a historical document that will be a source of record for later usage, such as repeating the survey or providing a basis for building upon the survey findings. In other words, it involves the formal write-up of conclusions.

Problems Encountered by Researchers in India

Researchers in India, particularly those engaged in empirical research, are facing several problems. Some of the important problems are as follows:

1. The lack of a scientific training in the methodology of research is a great impediment for researchers in our country. There is paucity of competent researchers. Many researchers take a leap in the dark without knowing research methods. Most of the work, which goes in the name of research, is not methodologically sound. Research, to many researchers and even to their guides, is mostly a scissor and paste job without any insight shed on the collated materials. The consequence is obvious, viz., the research results, quite often, do not reflect the reality or realities. Thus, a systematic study of research methodology is an urgent necessity. Before undertaking research projects, researchers should be well equipped with all the methodological aspects. As such, efforts should be made to provide short-duration intensive courses for meeting this requirement.

2. There is insufficient interaction between the university research departments on one side and business establishments, government departments and research institutions on the other side. A great deal of primary data of non-confidential nature remains untouched/untreated by the researchers for want of proper contacts. Efforts should be made to develop satisfactory liaison among all concerned for better and realistic researches.

3. Most of the business units in our country do not have the confidence that the material supplied by them to researchers will not be misused and as such they are often reluctant in supplying the needed information to researchers. The concept of secrecy seems to be sacrosanct to business organisations in the country so much so that it proves an impermeable barrier to researchers. Thus, there is the need for generating the confidence that the information data obtained from a business unit will not be misused.

4. Research studies overlapping one another are undertaken quite often for want of adequate information. This results in duplication and flutters away resources. This problem can be solved by proper compilation and revision, at regular intervals, of a list of subjects on which and the places where the research is going on. Due attention should be given toward identification of research problems in various disciplines of applied science which are of immediate concern to the industries.

5. There does not exist a code of conduct for researchers and inter-university and inter-departmental rivalries are also quite common. Hence, there is a need for developing a code of conduct for researchers which, if adhered sincerely, can win over this problem.

6. Many researchers in our country also face the difficulty of adequate and timely secretarial assistance, including computerial assistance. This causes unnecessary delays in the completion of research studies. All possible efforts are made in this direction so that efficient secretarial assistance is made available to researchers and that too well in time.

7. Library management and functioning is not satisfactory at many places and much of the time and energy of researchers are spent in tracing out the books, journals, reports, etc., rather than in tracing out relevant material from them.

8. There is also the problem that many of our libraries are not able to get copies of old and new acts/rules, reports and other government publications in time. This problem is felt more in libraries which are away in places from Delhi and/or the state capitals. Thus, efforts should be made for the regular and speedy supply of all governmental publications to reach our libraries.

9. There is also the difficulty of timely availability of published data from various government and other agencies doing this job in our country. Researcher also faces the problem on account of the fact that the published data vary quite significantly because of differences in coverage by the concerning agencies.

10. There may, at times, take place the problem of conceptualization and also problems relating to the process of data collection and related things.

Q.4. Discuss the managerial value of business research?

Ans. Managerial Value of Business Research

The prime managerial value of business research is that it reduces uncertainty by providing information that improves the decision-making process. The decision making process associated with the development and implementation of a strategy involves three interrelated stages.

1. Identifying problems or opportunities

2. Selecting and implementing a course of action

3. Evaluating the course of action

Business research, by supplying managers with pertinent information, may play an important role by reducing managerial uncertainty in each of these stages.

Identifying Problems or Opportunities

Before any strategy can be developed, an organization must determine where it wants to go and how it will get there. Business research can help managers plan strategies by determining the nature of situations by identifying the existence of problems or opportunities present in the organization.

Business research may be used as a diagnostic activity to provide information about what is occurring within an organization or in its environment. The mere description of some social or economic activity may familiarize managers with organizational and environmental occurrences and help them understand a situation. For example, the description of the dividend history of stocks in an industry may point to an attractive investment opportunity.

Information supplied by business research may also indicate problems. For example, employee interviews undertaken to delineate the dimensions of an airline reservation clerk’s job may reveal that reservation clerks emphasize competence in issuing tickets over courtesy and friendliness in customer contact. Once business research indicates a problem, managers may feel that the alternatives are clear enough to make a decision based on experience or intuition, or they may decide that more business research is needed to generate additional information for a better understanding of the situation.

Whether an organization recognizes a problem or gains insight into a potential opportunity, an important aspect of business research is its provision of information that identifies or clarifies alternative courses of action.

Selecting and implementing a course of action

After the alternative courses of action have been identified, business research is often conducted to obtain specific information that will aid in evaluating the alternatives and in selecting the best course of action. In such a case, business research can be designed to supply the exact information necessary to determine which course of action is best of the organization.

Opportunities may be evaluated through the use of various performance criteria. For example, estimates of market potential allow managers to evaluate the revenue that will be generated by each of the possible opportunities. A good forecast supplied by business researchers is among the most useful pieces of planning information a manager can have. Of course, complete accuracy in forecasting the future is not possible because change is constantly occurring in the business environment. Nevertheless, objective information generated by business research to forecast environmental occurrences may be the foundation for selecting a particular course of action.

Clearly, the best plan is likely to result in failure if it is not properly implemented. Business research may be conducted with the people who will be affected by a pending decision to indicate the specific tactics required to implement that course of action.

Evaluating course of action

After a course of action has been implemented, business research may serve as a tool to inform managers whether planned activities were properly executed and whether they accomplished what they were expected to accomplish. In other words, business research may be conducted to provide feedback for evaluation and control of strategies and tactics.

Evaluation research is the formal, objective measurement and appraisal of the extent to which a given action, activity, or program has achieved its objectives. In addition to measuring the extent to which completed programs achieved their objectives or to which continuing programs are presently performing as projected, evaluation research may provide information about the major factor influencing the observed performance levels.

When analysis of performance indicated that all is not going as planned, business research may be required to explain why something “went wrong.” Detailed information about specific mistakes or failures is frequently sought. If a general problem area is identified, breaking down industry sales volume and a firm’s sales volume into different geographic areas may provide an explanation of specific problems, and exploring these problems in greater depth may indicate which managerial judgments were erroneous.

Q.5. Define research design? Explain the characteristics and types of research design?

Ans. A research design is a framework or blueprint for conducting the research project. It gives details, of the procedures necessary for obtaining the information needed to structure or solve research problems. Although a broad approach to the problem has already been developed, the research design specifies the details-the nuts and bolts of implementing that approach. A research design lays the foundation for conducting the project. A good research design will ensure that the business research project is conducted effectively. The most important step after defining the research problem is preparing the design of the research project, which is popularly known as the ‘research design’. A research design helps to decide upon issues like what, when, where, how much, by what means etc. with regard to an enquiry or a research study. A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure. Thus, research design provides an outline of what the researcher is going to do in terms of framing the hypothesis, its operational implications and the final data analysis. Specifically, the research design highlights decisions which include:

            1. The nature of the study

2. The purpose of the study

3. The location where the study would be conducted

4. The nature of data required

5. From where the required data can be collected

6. What time period the study would cover

7. The type of sample design that would be used

8. The techniques of data collection that would be used

9. The methods of data analysis that would be adopted and

10. The manner in which the report would be prepared

In view of the stated research design decisions, the overall research design may be divided into the following:

a. The sampling design that deals with the method of selecting items to be observed for the selected study;

b. The observational design that relates to the conditions under which the observations are to be made;

c. The statistical design that concerns with the question of how many items are to be observed, and how the information and data gathered are to be analysed; and

d. The operational design that deals with the techniques by which the procedures specified in the sampling, statistical and observational designs can be carried out.

Features of Research Design:

The important features of Research Design may be outlined as follows:

i. It constitutes a plan that identifies the types and sources of information required for the research problem;

ii. It constitutes a strategy that specifies the methods of data collection and analysis which would be adopted; and

iii. It also specifies the time period of research and monetary budget involved in conducting the study, which comprise the two major constraints of undertaking any research

Concepts Relating To Research Design:

Some of the important concepts relating to Research Design are discussed below:

1. Dependent and Independent Variables:

A magnitude that varies is known as a variable. The concept may assume different quantitative values like height, weight, income etc. Qualitative variables are not quantifiable in the strictest sense of the term. However, the qualitative phenomena may also be quantified in terms of the presence or absence of the attribute(s) considered. The phenomena that assume different values quantitatively even in decimal points are known as ‘continuous variables’. But all variables need not be continuous. Values that can be expressed only in integer values are called ‘non-continuous variables’. In statistical terms, they are also known as ‘discrete variables’. For example, age is a continuous variable, whereas the number of children is a non-continuous variable. When changes in one variable depend upon the changes in other variable or variables, it is known as a dependent or endogenous variable, and the variables that cause the changes in the dependent variable are known as the independent or explanatory or exogenous variables. For example, if demand depends upon price, then demand is a dependent variable, while price is the independent variable. And, if more variables determine demand, like income and price of the substitute commodity, then demand also depends upon them in addition to the price of original commodity. In other words, demand is a dependent variable which is determined by the independent variables like price of the original commodity, income and price of substitutes.

2. Extraneous Variables:

The independent variables which are not directly related to the purpose of the study but affect the dependent variables, are known as extraneous variables. For instance, assume that a researcher wants to test the hypothesis that there is a relationship between children’s school performance and their self-confidence, in which case the latter is an independent variable and the former, a dependent variable. In this context, intelligence may also influence the school performance. However, since it is not directly related to the purpose of the study undertaken by the researcher, it would be known as an extraneous variable. The influence caused by the extraneous variable(s) on the dependent variable is technically called the ‘experimental error’. Therefore, a research study should always be framed in such a manner that the influence of extraneous variables on the dependent variable/s is completely controlled, and the influence of independent variable/s is clearly evident.

3. Control:

One of the most important features of a good research design is to minimize the effect of extraneous variable(s). Technically, the term ‘control’ is used when a researcher designs the study in such a manner that it minimizes the effects of extraneous variables. The term ‘control’ is used in experimental research to reflect the restrain in experimental conditions.

4. Confounded Relationship:

The relationship between the dependent and independent variables is said to be confounded by an extraneous variable, when the dependent variable is not free from its effects.

5. Research Hypothesis:

When a prediction or a hypothesized relationship is tested by adopting scientific methods, it is known as research hypothesis. The research hypothesis is a predictive statement which relates to a dependent variable and an independent variable. Generally, a research hypothesis must consist of at least one dependent variable and one independent variable. Whereas, the relationships that are assumed but not to be tested are predictive statements that are not to be objectively verified, thus are not classified as research hypotheses.

6. Experimental and Non-experimental Hypothesis Testing Research:

When the objective of a research is to test a research hypothesis, it is known as hypothesis-testing research. Such research may be in the nature of experimental design or non-experimental design. The research in which the independent variable is manipulated is known as ‘experimental hypothesis-testing research’, whereas the research in which the independent variable is not manipulated is termed as ‘non-experimental hypothesis-testing research’. For example, assume that a researcher wants to examine whether family income influences the school attendance of a group of students, by calculating the coefficient of correlation between the two variables. Such an example is known as a non-experimental hypothesis-testing research, because the independent variable - family income is not manipulated here. Again assume that the researcher randomly selects 150 students from a group of students who pay their school fees regularly and then classifies them into two sub-groups by randomly including 75 in Group A, whose parents have regular earning, and 75 in Group B, whose parents do not have regular earning. Assume that at the end of the study, the researcher conducts a test on each group in order to examine the effects of regular earnings of the parents on the school attendance of the student. Such a study is an example of experimental hypothesis-testing research, because in this particular study the independent variable regular earnings of the parents have been manipulated.

7. Experimental and Control Groups:

When a group is exposed to usual conditions in an experimental hypothesis-testing research, it is known as ‘control group’. On the other hand, when the group is exposed to certain new or special condition, it is known as an ‘experimental group’. In the afore-mentioned example, Group A can be called as control group and Group B as experimental group. If both the groups, A and B are exposed to some special feature, then both the groups may be called as ‘experimental groups’. A research design may include only the experimental group or both the experimental and control groups together.

8. Treatments:

Treatments refer to the different conditions to which the experimental and control groups are subject to. In the example considered, the two treatments are the parents with regular earnings and those with no regular earnings. Likewise, if a research study attempts to examine through an experiment the comparative effect of three different types of fertilizers on the yield of rice crop, then the three types of fertilizers would be treated as the three treatments.

9. Experiment:

Experiment refers to the process of verifying the truth of a statistical hypothesis relating to a given research problem. For instance, an experiment may be conducted to examine the yield of a certain new variety of rice crop developed. Further, Experiments may be categorized into two types, namely, ‘absolute experiment’ and ‘comparative experiment’. If a researcher wishes to determine the impact of a chemical fertilizer on the yield of a particular variety of rice crop, then it is known as absolute experiment. Meanwhile, if the researcher wishes to determine the impact of chemical fertilizer as compared to the impact of bio-fertilizer, then the experiment is known as a comparative experiment.

10. Experimental Unit(s):

Experimental units refer to the pre-determined plots, characteristics or the blocks, to which different treatments are applied. It is worth mentioning here that such experimental units must be selected with great caution.

Types of Research Design:

There are different types of research designs. They may be broadly categorized as:

(1) Exploratory Research Design;

(2) Descriptive and Diagnostic Research Design; and

(3) Hypothesis-Testing Research Design.

1. Exploratory Research Design:

The Exploratory Research Design is known as formulative research design. When a researcher has a limited amount of experience with or knowledge about a research issue, exploratory research is a useful preliminary step that helps ensure that a more rigorous, more conclusive future study will not begin with an inadequate understanding of the nature of the management problem. The findings discovered through exploratory research would lead the researcher to emphasize learning more about the particulars of the findings in subsequent conclusive studies. Conclusive research answers questions of fact necessary to determine course of action. This is never the purpose of exploratory research. The main objective of using such a research design is to formulate a research problem for an in-depth or more precise investigation, or for developing a working hypothesis from an operational aspect. The major purpose of such studies is the discovery of ideas and insights. Therefore, such a research design suitable for such a study should be flexible enough to provide opportunity for considering different dimensions of the problem under study. The in-built flexibility in research design is required as the initial research problem would be transformed into a more precise one in the exploratory study, which in turn may necessitate changes in the research procedure for collecting relevant data. Usually, the following three methods are considered in the context of a research design for such studies. They are (a) a survey of related literature; (b) experience survey; and (c) analysis of ‘insight-stimulating’ instances.

Why conduct exploratory research?

The purpose of exploratory research is intertwined with the need for a clear and precise statement of the recognized problem. Three interrelated forms of exploratory research exist: (1) diagnosing a situation, (2) screening alternatives, and (3) discovering new ideas. Diagnosing a Situation

Much has already been said about the need for situation analysis to clarity a problem’s nature. Exploratory research helps diagnose the dimensions of problems so that successive research projects will be on target. It helps set priorities for research. In some cases exploratory research provides an orientation for management by gathering information on a topic with which management has little experience. Although a research project has not yet been planned, information about an issue is needed before the appropriate action can be developed.

Personnel research managers often conduct exploratory research as a diagnostic tool to point out issues of employee concern’ or to generate possible explanations for motivational patterns. For example, preliminary interviews with employees may be utilized to learn current “hot” issues, as well as concerns about bread-and-butter issues such as wages, working conditions, career opportunities, and the like.

Screening Alternative

When several opportunities arise but the budget precludes investigating all possible options, exploratory research may be used to determine the best alternatives. Many crystallizes good investments were not made because a company chose to invest in something better. Some new organizational structures are found t6 be unworkable. In an exploratory look at market data (size, number, and so on), a product alternative, may informally not be feasible because the market is too small. Although this aspect of exploratory research is not a substitute for conclusive research, certain evaluative information can be acquired in exploratory studies.

The need for concept testing is a frequent reason for conducting exploratory research. Concept testing is a general term or many different research procedures, all of which have the same purpose. It refers to those research procedures that test some sort of stimulus as a proxy for a new or revised program, product, or service. Typically, test subjects are presented with an idea and asked if they liked it, and so-on. Concept testing is a means of evaluating ideas by providing a “feel” for the merits and idea prior to the commitment of research and development, manufacturing, or other company resources. Researchers look for trouble in business signals in evaluations of concepts in order to avoid future problems in business research.

Concept testing may portray the functions, uses, and possible situations for a proposed product. For example, Del Monte conducted a concept test to determine if consumers would accept the idea of shelf-stable yogurt. The plan was scrapped after survey showed that buyers refused to accept the idea that yogurt could be kept unrefrigerated. Early research indicated that such a concept was viewed as desirable and unique, but the cost of achieving believability finally judged to be high.

In other cases, when subjects have expressed reservations about certain aspects of the idea but the general concept has not been evaluated negatively, researchers know that the concept needs to be refined. The intangibles influencing brand image, product appearance, name and price– as well as a description of the product simulate reality. Thus, prior to actual product development, the idea expressing the nature of the brand is conveyed to the test subjects.

Discovering New Ideas

Exploratory research is often used to generate new ideas. Perhaps factory workers have suggestions for increasing production, or improving safety. Consumers may suggest hew product ideas, or unthought-of problems might be identified. 

For example, an automobile manufacturer might have drivers design their dream influencing cars on video screens using computerized design software adapted from programs used by automotive designers. This exploratory research generates ideas that would never have occurred to the firm’s design staff.

A manager may choose from four general categories of exploratory research methods: (1) experience surveys, (2) secondary data analysis, (3) case studies, and (4) pilot studies. Each category provides various alternative ways of gathering information.

2. Descriptive and Diagnostic Research Design:

A Descriptive Research Design is concerned with describing the characteristics of a particular individual or a group. Meanwhile, a diagnostic research design determines the frequency with which a variable occurs or its relationship with another variable. In other words, the study analyzing whether a certain variable is associated with another comprises a diagnostic research study. On the other hand, a study that is concerned with specific predictions or with the narration of facts and characteristics related to an individual, group or situation, are instances of descriptive research studies. Generally, most of the social research design falls under this category. As a research design, both the descriptive and diagnostic studies share common requirements, hence they are grouped together. However, the procedure to be used and the research design need to plan carefully. The research design must also make appropriate provision for protection against bias and thus maximize reliability, with due regard to the completion of the research study in an economical manner. The research design in such studies should be rigid and not flexible. Besides, it must also focus attention on the following:

a) Formulation of the objectives of the study,

b) Proper designing of the methods of data collection,

c) Sample selection,

d) Data collection,

e) Processing and analysis of the collected data, and

f) Reporting the findings.

Six W’s

1.      Who: Who should be considered a patron of a particular departmental store?

2.      What: What information should be obtained from the respondents?

3.      When: When should the information be obtained from the respondents?

4.      Where: Where should the respondents is contacted to obtain the required information?

5.      Why: Why are we obtaining information from the respondents?

6.      Way: In what are we going to obtain information from the respondents?

As the name implies, the major objective of descriptive research is to describe something usually market characteristics or functions. Descriptive research is conducted for the following reasons:

1. To describe the characteristics of relevant groups, such as consumers, salespeople, organizations, or market areas.

2. To estimate the percentage of units in a specified population exhibiting a certain behavior; for example, the percentage of heavy users of prestigious department stores who also patronize discount department stores.

3. To determine the perceptions of product characteristics. For example, how do households’ perceive the various department stores in terms of salient factors of the choice criteria?

4. To determine the degree to which marketing variables are associated. For example, to what extent is shopping at department stores related to eating out?

5. To make specific predictions.

Descriptive research assumes that the researcher has much prior knowledge about the problem situation. In fact, a major difference between exploratory and descriptive research is that descriptive research is characterized by the prior formulation of specific hypotheses. Thus, the information needed is clearly defined. As a result, descriptive research is pre-planned and structured.

It is typically based on large representative samples. A formal research design specifies the methods for selecting the sources of information and for collecting data from those sources. A descriptive design requires a clear specification of the who, what, when, where, why, and way (the six Ws) of the research. These, and other similar questions, should be asked until the information to be obtained has been clearly defined.

In summary, descriptive research, in contrast to exploratory research, is marked by a clear statement of the problem, specific hypotheses, and detailed information needs. The survey conducted in the department store patronage project, which involved personal interviews, is an example of descriptive research. Other examples of descriptive studies are:

• Market studies, which describe the size of the market, buying power of the consumer’s availability of distributors, and consumer profiles.

• Market share studies, which determine the proportion of total sales received by a company and its competitors.

3. Hypothesis-Testing Research Design:

Hypothesis-Testing Research Designs are those in which the researcher tests the hypothesis of causal relationship between two or more variables. These studies require procedures that would not only decrease bias and enhance reliability, but also facilitate deriving inferences about the causality. Generally, experiments satisfy such requirements. Hence, when research design is discussed in such studies, it often refers to the design of experiments.

Characteristics of a Good Research Design:

A good research design often possesses the qualities of being flexible, suitable, efficient, and economical and so on. Generally, a research design which minimizes bias and maximizes the reliability of the data collected and analysed is considered a good design. A research design which does not allow even the smallest experimental error is said to be the best design for investigation. Further, a research design that yields maximum information and provides an opportunity of viewing the various dimensions of a research problem is considered to be the most appropriate and efficient design. Thus, the question of a good design relates to the purpose or objective and nature of the research problem studied. While a research design may be good, it may not be equally suitable to all studies. In other words, it may be lacking in one aspect or the other in the case of some other research problems. Therefore, no single research design can be applied to all types of research problems.

A research design suitable for a specific research problem would usually involve the following considerations:

i. The methods of gathering the information;

ii. The skills and availability of the researcher and his/her staff, if any;

iii. The objectives of the research problem being studied;

iv. The nature of the research problem being studied; and

        v. The available monetary support and duration of time for the research work.

Q.6. Define the concept of sampling design. Describe the steps involved in sampling design.

Ans. Sample Survey:

A sample design is a definite plan for obtaining a sample from a given population. Sample constitutes a certain portion of the population or universe. Sampling design refers to the technique or the procedure the researcher adopts for selecting items for the sample from the population or universe. A sample design helps to decide the number of items to be included in the sample, i.e., the size of the sample. The sample design should be determined prior to data collection. There are different kinds of sample designs which a researcher can choose. Some of them are relatively more precise and easier to adopt than the others. A researcher should prepare or select a sample design, which must be reliable and suitable for the research study proposed to be undertaken.

Steps in Sampling Design:

A researcher should take into consideration the following aspects while developing a sample design:

1) Type of Universe:

The first step involved in developing sample design is to clearly define the number of cases, technically known as the universe. A universe may be finite or infinite. In a finite universe the number of items is certain, whereas in the case of an infinite universe the number of items is infinite (i.e., there is no idea about the total number of items). For example, while the population of a city or the number of workers in a factory comprise finite universes, the number of stars in the sky, or throwing of a dice represent infinite universe.

2) Sampling Unit:

Prior to selecting a sample, decision has to be made about the sampling unit. A sampling unit may be a geographical area like a state, district, village, etc., or a social unit like a family, religious community, school, etc., or it may also be an individual. At times, the researcher would have to choose one or more of such units for his/her study.

3) Source List:

Source list is also known as the ‘sampling frame’, from which the sample is to be selected. The source list consists of names of all the items of a universe. The researcher has to prepare a source list when it is not available. The source list must be reliable, comprehensive, correct, and appropriate. It is important that the source list should be as representative of the population as possible.

4) Size of Sample:

Size of the sample refers to the number of items to be chosen from the universe to form a sample. For a researcher, this constitutes a major problem. The size of sample must be optimum. An optimum sample may be defined as the one that satisfies the requirements of representativeness, flexibility, efficiency, and reliability. While deciding the size of sample, a researcher should determine the desired precision and the acceptable confidence level for the estimate. The size of the population variance should be considered, because in the case of a larger variance generally a larger sample is required. The size of the population should be considered, as it also limits the sample size. The parameters of interest in a research study should also be considered, while deciding the sample size. Besides, costs or budgetary constraint also plays a crucial role in deciding the sample size.

5) Budgetary Constraint:

From the practical point of view, cost considerations exercise a major influence on the decisions related to not only the sample size, but also on the type of sample selected. Thus, budgetary constraint could also lead to the adoption of a non-probability sample design.

6) Sampling Procedure:

Finally, the researcher should decide the type of sample or the technique to be adopted for selecting the items for a sample. This technique or procedure itself may represent the sample design. There are different sample designs from which a researcher should select one for his/her study. It is clear that the researcher should select that design which, for a given sample size and budget constraint, involves a smaller error.

Characteristics of a Good Sample Design:

The following are the characteristic features of a good sample design:

a. The sample design should yield a truly representative sample;

b. The sample design should be such that it results in small sampling error;

c. The sample design should be viable in the context of budgetary constraints of the research study;

d. The sample design should be such that the systematic bias can be controlled; and

e. The sample must be such that the results of the sample study would be applicable, in general, to the universe at a reasonable level of confidence.

Different Types of Sample Designs:

Sample designs may be classified into different categories based on two factors, namely, the representation basis and the element selection technique. Under the representation basis, the sample may be classified as:

I. Non-probability sampling

II. Probability sampling

While probability sampling is based on random selection, the non-probability sampling is based on ‘non-random’ selection of samples.

I. Non-Probability Sampling:

Non-probability sampling is the sampling procedure that does not afford any basis for estimating the probability that each item in the population would have an equal chance of being included in the sample. Non-probability sampling is also known as deliberate sampling, judgment sampling and purposive sampling. Under this type of sampling, the items for the sample are deliberately chosen by the researcher; and his/her choice concerning the choice of items remains supreme. In other words, under non-probability sampling the researchers select a particular unit of the universe for forming a sample on the basis that the small number that is thus selected out of a huge one would be typical or representative of the whole population. For example, to study the economic conditions of people living in a state, a few towns or village may be purposively selected for an intensive study based on the principle that they are representative of the entire state. In such a case, the judgment of the researcher of the study assumes prime importance in this sampling design.

Quota Sampling:

Quota sampling is also an example of non-probability sampling. Under this sampling, the researchers simply assume quotas to be filled from different strata, with certain restrictions imposed on how they should be selected. This type of sampling is very convenient and is relatively less expensive. However, the samples selected using this method certainly do not satisfy the characteristics of random samples. They are essentially judgment samples and inferences drawn based on that, would not be amenable to statistical treatment in a formal way.

II. Probability Sampling:

Probability sampling is also known as ‘choice sampling’ or ‘random sampling’. Under this sampling design, every item of the universe has an equal chance of being included in the sample. In a way, it is a lottery method under which individual units are selected from the whole group, not deliberately, but by using some mechanical process. Therefore, only chance would determine whether an item or the other would be included in the sample or not. The results obtained from probability or random sampling would be assured in terms of probability. That is, the researcher can measure the errors of estimation or the significance of results obtained from the random sample. This is the superiority of random sampling design over the deliberate sampling design. Random sampling satisfies the law of statistical regularity, according to which if on an average the sample chosen is random, then it would have the same composition and characteristics of the universe. This is the reason why the random sampling method is considered the best technique of choosing a representative sample.

The following are the implications of the random sampling:

i. It provides each element in the population an equal probable chance of being chosen in the sample, with all choices being independent of one another and

ii. It offers each possible sample combination an equal probable opportunity of being selected.

Method of Selecting a Random Sample:

The process of selecting a random sample involves writing the name of each element of a finite population on a slip of paper and putting them into a box or a bag. Then they have to be thoroughly mixed and then the required number of slips for the sample can be picked one after the other without replacement. While doing this, it has to be ensured that in successive drawings each of the remaining elements of the population has an equal chance of being chosen. This method results in the same probability for each possible sample.

Q.7. Distinguish between probability and non-probability sampling?

Ans. Under restricted sampling technique, the probability sampling may result in complex random sampling designs. Such designs are known as mixed sampling designs. Many of such designs may represent a combination of non-probability and probability sampling procedures in choosing a sample.

Some of the prominent complex random sampling designs are as follows:

(i) Systematic Sampling:

In some cases, the best way of sampling is to select every first item on a list. Sampling of this kind is called as systematic sampling. An element of randomness is introduced in this type of sampling by using random numbers to select the unit with which to start. For example, if a 10 per cent sample is required out of 100 items, the first item would be selected randomly from the first low of item and thereafter every 10th item. In this kind of sampling, only the first unit is selected randomly, while rest of the units of the sample is chosen at fixed intervals.

(ii) Stratified Sampling:

When a population from which a sample is to be selected does not comprise a homogeneous group, stratified sampling technique is generally employed for obtaining a representative sample. Under stratified sampling, the population is divided into many sub-populations in such a manner that they are individually more homogeneous than the rest of the total population. Then, items are selected from each stratum to form a sample. As each stratum is more homogeneous than the remaining total population, the researcher is able to obtain a more precise estimate for each stratum and by estimating each of the component parts more accurately; he/she is able to obtain a better estimate of the whole. In sum, stratified sampling method yields more reliable and detailed information.

(iii) Cluster Sampling:

When the total area of research interest is large, a convenient way in which a sample can be selected is to divide the area into a number of smaller non-overlapping areas and then randomly selecting a number of such smaller areas. In the process, the ultimate sample would consist of all the units in these small areas or clusters. Thus in cluster sampling, the total population is sub-divided into numerous relatively smaller subdivisions, which in themselves constitute clusters of still smaller units. And then, some of such clusters are randomly chosen for inclusion in the overall sample.

(iv) Area Sampling:

When clusters are in the form of some geographic subdivisions, then cluster sampling is termed as area sampling. That is, when the primary sampling unit represents a cluster of units based on geographic area, the cluster designs are distinguished as area sampling. The merits and demerits of cluster sampling are equally applicable to area sampling.

(v) Multi-Stage Sampling:

A further development of the principle of cluster sampling is multi-stage sampling. When the researcher desires to investigate the working efficiency of nationalized banks in India and a sample of few banks is required for this purpose, the first stage would be to select large primary sampling unit like the states in the country. Next, certain districts may be selected and all banks interviewed in the chosen districts. This represents a two-stage sampling design, with the ultimate sampling units being clusters of districts.

On the other hand, if instead of taking census of all banks within the selected districts, the researcher chooses certain towns and interviews all banks in it, this would represent three-stage sampling design. Again, if instead of taking a census of all banks within the selected towns, the researcher randomly selects sample banks from each selected town, then it represents a case of using a four-stage sampling plan. Thus, if the researcher selects randomly at all stages, then it is called as multi-stage random sampling design.

(vi) Sampling with Probability Proportional To Size:

When the case of cluster sampling units does not have exactly or approximately the same number of elements, it is better for the researcher to adopt a random selection process, where the probability of inclusion of each cluster in the sample tends to be proportional to the size of the cluster. For this, the number of elements in each cluster has to be listed, irrespective of the method used for ordering it. Then the researcher should systematically pick the required number of elements from the cumulative totals. The actual numbers thus chosen would not however reflect the individual elements, but would indicate as to which cluster and how many from them are to be chosen by using simple random sampling or systematic sampling. The outcome of such sampling is equivalent to that of simple random sample. The method is also less cumbersome and is also relatively less expensive.

Thus, a researcher has to pass through various stages of conducting research once the problem of interest has been selected. Research methodology familiarizes a researcher with the complex scientific methods of conducting research, which yield reliable results that are useful to policy-makers, government, industries etc. in decision-making.

UNIT II

Q.8. Differentiate between primary and secondary data?

Ans. The most important aspect of research is data collection. With the help of data, the information can be presented in such a manner so that the same may be useful for decision making by the managers. Data are nothing but the information. The data are name after the source. While collecting data, reliability and accuracy should be maintained. In the whole process of gathering information, the source of data should be taken care of very seriously. Data can be obtained from primary or secondary sources. Primary data refer to information obtained first hand by the researcher on the variables of interest for the specific purpose of the study. Secondary data refer to information gathered from sources already existing. Primary data refers to the data collected for the first time, whereas secondary data refers to the data that have already been collected and used earlier by somebody or some agency. Both the sources of information have their merits and demerits. The selection of a particular source depends upon the (a) purpose and scope of enquiry, (b) availability of time, (c) availability of finance, (d) accuracy required, (e) statistical tools to be used, (f) sources of information (data), and (g) method of data collection.

Some examples of sources of primary data are individuals, focus groups, panels of respondents specifically set up by the researcher and from whom opinions may be sought on specific issues from time to time, or some unobtrusive sources such as a trash can. The internet could also serve as a primary data source when questionnaires are administered over it. Data can also be obtained from secondary sources, as for example, company records or achieves, government publications, industry analyses offered by the media, web sites, the internet, and so on.

Basis of difference	Primary data	Secondary data
Originality	Primary data are collected originally	Secondary dada are already available and thus these are not original
Collection	By the investigator himself	By some other person
Time	More time consuming	Less time consuming
Precaution	Needs more precaution at the time of collection but less at the time of its use	Needs less precaution at the time of collection but more at the time of its use
Conversion	A primary data after a use is converted into a secondary data	It can never be converted into a primary data
Statistical process	Not done	Done
Cost	Expensive	Cheaper
Efforts	More efforts required	Less efforts required
Accuracy	More accurate	Less accurate
Training personnel required	Experts/trained required	Less trained personnel

Q.9. Explain the different methods of collecting primary data with their relative merits and demerits?

Ans. METHODS OF COLLECTING PRIMARY DATA

Primary data may be obtained by applying any of the following methods:

1. Direct Personal Interviews.

2. Indirect Oral Interviews.

3. Information from Correspondents.

4. Mailed Questionnaire Methods.

5. Schedule Sent Through Enumerators.

1. Direct Personal Interviews:

A face to face contact is made with the informants (persons from whom the information is to be obtained) under this method of collecting data. The interviewer asks them questions pertaining to the survey and collects the desired information. Thus, if a person wants to collect data about the working conditions of the workers of the Tata Iron and Steel Company, Jamshedpur, he would go to the factory, contact the workers and obtain the desired information. The information collected in this manner is first hand and also original in character. There are many merits and demerits of this method, which are discussed as under:

Merits:

1. Most often respondents are happy to pass on the information required from them when contacted personally and thus response is encouraging.

2. The information collected through this method is normally more accurate because interviewer can clear doubts of the informants about certain questions and thus obtain correct information. In case the interviewer apprehends that the informant is not giving accurate information, he may cross-examine him and thereby try to obtain the information.

3. This method also provides the scope for getting supplementary information from the informant, because while interviewing it is possible to ask some supplementary questions which may be of greater use later.

4. There might be some questions which the interviewer would find difficult to ask directly, but with some tactfulness, he can mingle such questions with others and get the desired information. He can twist the questions keeping in mind the informant’s reaction. Precisely, a delicate situation can usually he handled more effectively by a personal interview than by other survey techniques.

5. The interviewer can adjust the language according to the status and educational level of the person interviewed, and thereby can avoid inconvenience and misinterpretation on the part of the informant.

Demerits:

1. This method can prove to be expensive if the number of informants is large and the area is widely spread.

2. There is a greater chance of personal bias and prejudice under this method as compared to other methods.

3. The interviewers have to be thoroughly trained and experienced; otherwise they may not be able to obtain the desired information. Untrained or poorly trained interviewers may spoil the entire work.

4. This method is more time taking as compared to others. This is because interviews can be held only at the convenience of the informants. Thus, if information is to be obtained from the working members of households, interviews will have to be held in the evening or on week end. Even during evening only an hour or two can be used for interviews and hence, the work may have to be continued for a long time, or a large number of people may have to be employed which may involve huge expenses.

In the present time of extreme advancement in the communication system, the investigator instead of going personally and conducting a face to face interview may also obtain information over telephone. A good number of surveys are being conducted every day by newspapers and television channels by sending the reply either by e-mail or SMS. This method has become very popular nowadays as it is less expensive and the response is extremely quick. But this method suffers from some serious defects, such as (a) those who own a phone or a television only can be approached by this method, (b) only few questions can be asked over phone or through television, (c) the respondents may give a vague and reckless answers because answers on phone or through SMS would have to be very short.

2. Indirect Oral Interviews:

Under this method of data collection, the investigator contacts third parties generally called ‘witnesses’ who are capable of supplying necessary information. This method is generally adopted when the information to be obtained is of a complex nature and informants are not inclined to respond if approached directly. For example, when the researcher is trying to obtain data on drug addiction or the habit of taking liquor, there is high probability that the addicted person will not provide the desired data and hence will disturb the whole research process. In this situation taking the help of such persons or agencies or the neighbours who know them well becomes necessary. Since these people know the person well, they can provide the desired data. Enquiry Committees and Commissions appointed by the Government generally adopt this method to get people’s views and all possible details of the facts related to the enquiry.

Therefore, for the success of this method it is necessary that the evidence of one person alone is not relied upon. Views from other persons and related agencies should also be ascertained to find the real position .Utmost care must be exercised in the selection of these persons because it is on their views that the final conclusions are reached.

3. Information from Correspondents:

The investigator appoints local agents or correspondents in different places to collect information under this method. These correspondents collect and transmit the information to the central office where data are processed. This method is generally adopted by newspaper agencies. Correspondents who are posted at different places supply information relating to such events as accidents, riots, strikes, etc., to the head office. The correspondents are generally paid staff or sometimes they may be honorary correspondents also. This method is also adopted generally by the government departments in such cases where regular information is to be collected from a wide area. For example, in the construction of a wholesale price index numbers regular information is obtained from correspondents appointed in different areas. The biggest advantage of this method is that, it is cheap and appropriate for extensive investigation. But a word of caution is that it may not always ensure accurate results because of the personal prejudice and bias of the correspondents. As stated earlier, this method is suitable and adopted in those cases where the information is to be obtained at regular intervals from a wide area.

4. Mailed Questionnaire Method:

Under this method, a list of questions pertaining to the survey which is known as ‘Questionnaire’ is prepared and sent to the various informants by post. Sometimes the researcher himself too contacts the respondents and gets the responses related to various questions in the questionnaire. The questionnaire contains questions and provides space for answers. A request is made to the informants through a covering letter to fill up the questionnaire and send it back within a specified time. The questionnaire studies can be classified on the basis of:

i. The degree to which the questionnaire is formalized or structured.

ii. The disguise or lack of disguise of the questionnaire and

iii. The communication method used.

When no formal questionnaire is used, interviewers adapt their questioning to each interview as it progresses. They might even try to elicit responses by indirect methods, such as showing pictures on which the respondent comments. When a researcher follows a prescribed sequence of questions, it is referred to as structured study. On the other hand, when no prescribed sequence of questions exists, the study is non-structured.

When questionnaires are constructed in such a way that the objective is clear to the respondents then these questionnaires are known as non- disguised; on the other hand, when the objective is not clear, the questionnaire is a disguised one. On the basis of these two classifications, four types of studies can be distinguished:

1. Non-disguised structured,

2. Non-disguised non-structured,

3. Disguised structured and

4. Disguised non-structured.

There are certain merits and demerits of this method of data collection which are discussed below:

Merits:

1. Questionnaire method of data collection can be easily adopted where the field of investigation is very vast and the informants are spread over a wide geographical area.

2. This method is relatively cheap and expeditious provided the informants respond in time.

3. This method has proved to be superior when compared to other methods like personal interviews or telephone method. This is because when questions pertaining to personal nature or the ones requiring reaction by the family are put forth to the informants, there is a chance for them to be embarrassed in answering them.

Demerits:

1. This method can be adopted only where the informants are literates so that they can understand written questions and lend the answers in writing.

2. It involves some uncertainty about the response. Co-operation on the part of informants may be difficult to presume.

3. The information provided by the informants may not be correct and it may be difficult to verify the accuracy.

However, by following the guidelines given below, this method can be made more effective:

The questionnaires should be made in such a manner that they do not become an undue burden on the respondents; otherwise the respondents may not return them back.

i. Prepaid postage stamp should be affixed

ii. The sample should be large

iii. It should be adopted in such enquiries where it is expected that the respondents would return the questionnaire because of their own interest in the enquiry.

iv. It should be preferred in such enquiries where there could be a legal compulsion to provide the information.

5. Schedules Sent Through Enumerators:

Another method of data collection is sending schedules through the enumerators or interviewers. The enumerators contact the informants, get replies to the questions contained in a schedule and fill them in their own handwriting in the questionnaire form. There is difference between questionnaire and schedule. Questionnaire refers to a device for securing answers to questions by using a form which the respondent fills in himself, whereas schedule is the name usually applied to a set of questions which are asked in a face-to face situation with another person. This method is free from most of the limitations of the mailed questionnaire method.

Merits:

The main merits or advantages of this method are listed below:

1. It can be adopted in those cases where informants are illiterate.

2. There is very little scope of non-response as the enumerators go personally to obtain the information.

3. The information received is more reliable as the accuracy of statements can be checked by supplementary questions wherever necessary.

This method too like others is not free from defects or limitations. The main limitations are listed below:

Demerits:

1. In comparison to other methods of collecting primary data, this method is quite costly as enumerators are generally paid persons.

2. The success of the method depends largely upon the training imparted to the enumerators.

3. Interviewing is a very skilled work and it requires experience and training. Many statisticians have the tendency to neglect this extremely important part of the data collecting process and this result in bad interviews. Without good interviewing most of the information collected may be of doubtful value.

4. Interviewing is not only a skilled work but it also requires a great degree of politeness and thus the way the enumerators conduct the interview would affect the data collected. When questions are asked by a number of different interviewers, it is possible that variations in the personalities of the interviewers will cause variation in the answers obtained. This variation will not be obvious. Hence, every effort must be made to remove as much of variation as possible due to different interviewers.

Observation Method

The observation method is the most commonly used method especially in studies relating to behavioural sciences. In a way we all observe things around us, but this sort of observation is not scientific observation. Observation becomes a scientific tool and the method of data collection for the researcher, when it serves a formulated research purpose, is systematically planned and recorded and is subjected to checks and controls on validity and reliability. Under the observation method, the information is sought by way of investigator’s own direct observation without asking from the respondent. For instance, in a study relating to consumer behaviour, the investigator instead of asking the brand of wristwatch used by the respondent, may himself look at the watch. The main advantage of this method is that if observation is done accurately. Secondly, the information obtained under this method relates to what is currently happening; it is not complicated by either the past behaviour or future intentions or attitudes. Thirdly, this method is independent of respondents’ willingness to respond and as such is relatively less demanding of active cooperation on the part of respondents as happens to be the case in the interview or the questionnaire method. This method is particularly suitable in studies which deal with subjects (i.e. respondents) who are not capable of giving verbal reports of their feelings for one reason or the other.

“However, observation method has various limitations. Firstly, it is an expensive method. Secondly, the information provided by this method is very limited. Thirdly, sometimes, unforeseen factors may interfere with the observational task. At times, the fact that some people are rarely accessible to direct observation creates obstacle for this method to collect data effectively.

While using this method, the researcher should keep in mind things like: What should be observed? How the observations should be recorded? Or how the accuracy of observation can be ensured? In case the observation is characterized by a careful definition of the units to be observed, the style of characterized by a careful definition of the units to be observed, the style of recording the observed information, standardized conditions of observations and the selection of pertinent data of observation, then the observation is called as structured observation. But when observation is to take place without these characteristics to be thought of in advance, the same is termed as unstructured observation. Structured observation is considered appropriate in descriptive studies, whereas in an exploratory study the observational procedure is most likely to be relatively unstructured.

We often talk about participant and non-participant types of observation in the context of studies, particularly of social sciences. This distinction depends upon the observer’s sharing or not sharing the life of the group he is observing. If the observer observes by making himself, more or less, a member of the group he is observing so that he can experience what the members of the group experience, the observation is called as the participant observation. But when the observer observes as a detached emissary without any attempt on his part to experience through participation what others feel, the observation of this type is often termed as non-participant observation. (When the observer is observing in such a manner that his presence may be unknown to the people he is observing, such an observation is described as disguised observation).

There are several merits of the participant type of observation: (i) the researcher is enabled to record the natural behaviour of the group. (ii) the researcher can even gather information which could not easily be obtained if he observes in a disinterested fashion. (iii) The researcher can even verify the truth of statements made by informants in the context of a questionnaire or a schedule. But there are also certain demerits of this type of observation viz., the observer may lose the objectivity to the extent he participates emotionally; the problem of observation-control is not solved; and it may narrow-down the researcher’s range of experience.

Sometimes we talk of controlled and uncontrolled observation. If the observation takes place in the natural setting, it may be termed as uncontrolled observation, but when observation takes place according to definite pre-arranged plans, involving experimental procedure, the same is then termed controlled observation. In non-controlled observation, no attempt is made to use precision instruments. The major aim of this type of observation is to get a spontaneous picture of life and persons. It has a tendency to supply naturalness and completeness of behaviour, allowing sufficient time for observing it. But in controlled observation, we use mechanical (or precision) instruments as aids to accuracy and standardization. Such observation has a tendency to supply formalized data upon which generalizations can be built with some degree of assurance. The main pitfall of non-controlled observation is that of subjective interpretation. There is also the danger of having the feeling that we know more about the observed phenomena than we actually do. Generally, controlled observation takes place in various experiments that are carried out in a laboratory or under controlled conditions, whereas uncontrolled observation is resorted to in case of exploratory researches.

Data collection through mechanical observation

There are situations where machines can provide data by recording the events of interest as they occur, without a researcher being physically present. Nielsen ratings is an oft-cited example in this regard. Other examples include collection of details of products sold by types of brands tracked through optical scanners and bar codes at the checkout stand, and tracking systems keeping a record of how many individuals utilize a facility or visit a web site. Films and electronic recording devices such as video cameras can also be used to record data. Such mechanically observed data are error-free.

Projective methods

Certain ideas and thoughts that cannot be easily verbalized or that remain at the unconscious levels in the respondents’ minds can usually be brought to the surface through motivational research. This is typically done by trained professionals who apply different probing techniques in order to bring to the surface deep-rooted ideas and thoughts in the respondents. Familiar techniques for gathering such data are word associations, sentence completion, thematic apperception tests (TAT), inkblot tests, and the like.

Word association techniques, such as asking the respondent to quickly associate a word-say, work-with the first thing that comes to mind, are often used to get at the true attitudes and feelings. The reply would be an indication of what work means to the individual. Similarly, sentence completion would have the respondent quickly complete a sentence, such as “work is –“. One respondent might say, “Work is a lot of fun”, whereas another might say “Work is drudgery”. These responses may provide some insights into individuals’ feelings and attitudes toward work.

Thematic apperception tests (TAT) call for the respondent to weave a story around a picture that is shown. Several need patterns and personality characteristics of employees could be traced through these tests. Inkblot tests, another form of motivational research, use coloured inkblots that are interpreted by the respondents, who explain what they see in the various patterns and colours.

Although these types of projective tests are useful for tapping attitudes and feelings that are difficult to obtain otherwise, they cannot be resorted to by researchers who are not trained to conduct motivational research. Consumer preferences, buying attitudes and behaviours, product development and other marketing research strategies make substantial use of in-depth probing. TAT and inkblot tests are on their way out in marketing research since advertisers and others now use the sentence completion tests and word association tests more frequently. Sketch drawings, Collages from magazine pictures, filling in the balloon captions of cartoon characters, and other strategies are also being followed to see how individuals associate different products, brands, advertisements, and so on, in their minds. Agencies frequently ask subjects to sketch “typical” users of various brands and narrate stories about them. The messages conveyed through the unsophisticated drawings are said to be very powerful, helping the development of different marketing strategies.

The idea behind motivational research is that “emotionality” (“I identify with it” feeling) rather than “rationality” (“it is good for me” thought), which is what keeps a product or practice alive, is captured. Emotions are powerful motivators of actions, and knowledge of what motivates individuals to act is very useful. The failure of attempts to trade in the “New Coke” for “Classic Coke” is an oft-cited example of the emotional aspect. Emotionality is clearly at the non-rational, subconscious level, lending itself to capture by projective techniques alone.

Modern technology is increasingly playing a key role in shaping data collection methods. Computer-assisted surveys, which help both interviewing as well as preparing and administering questionnaire electronically, are on the increase. Computer-assisted telephone interviewing (CATI), interactive electronic telephonic surveys, as well as administering questionnaires through electronic mail (e-mail), are now being used to facilitate data gathering.

Focus groups

Focus groups consist typically of 8 to 10 members with a moderator leading the discussions for about 2 hours on a particular topic, concept, or product. Members are generally chosen on the basis of their expertise in the topic on which information is sought. For example, computer specialists may be selected to form a focus group to discuss matters related to computers and computing, and women with children may compose the focus group to identify how organizations can help working mothers. The focus sessions are aimed at obtaining respondents impressions, interpretations, and opinions, as the members talk about the event, concept, product, or service. The moderator plays a vital role in steering the discussions in a manner that would draw out the information sought and keeping the members on track.

Focus group discussions on a specific topic at a particular location and at a specified time provide the opportunity for a flexible, free-flowing format for the members. The unstructured and spontaneous responses are expected to reflect the genuine opinions, ideas, and feelings of the members about the topic under discussion. Focus groups are relatively inexpensive and can provide fairly dependable data within a short time frame.

Face-to-face and telephone interviews

Interviews can be conducted either face to face or over the telephone. They could also be computer-assisted. Although most unstructured interviews in organizational research are conducted face-to-face, structured interviews could be either face to face or through the medium of the telephone, depending on the level of complexity of the issues involved, the likely duration of the interview, the convenience of both parties, and the geographical area covered by the survey. Telephone interviews are best suited when information from a large number of respondents spread over a wide geographical areas is to be obtained quickly, and the likely duration of each interview is, say, 10 minutes or less. Many market surveys, for instance, are conducted through structured telephone interviews. In addition, computer-assisted telephone interviews (CATI) are also possible, and easy to manage.

Secondary Data:

As stated earlier, secondary data are those data which have already been collected and analyzed by some earlier agency for its own use, and later the same data are used by a different agency. According to W.A.Neiswanger, “A primary source is a publication in which the data are published by the same authority which gathered and analyzed them. A secondary source is a publication, reporting the data which was gathered by other authorities and for which others are responsible.”

Sources of Secondary Data:

The various sources of secondary data can be divided into two broad categories:

1. Published sources, and

2. Unpublished sources.

1. Published Sources:

The governmental, international and local agencies publish statistical data, and chief among them are explained below:

(a) International Bublications: There are some international institutions and bodies like I.M.F, I.B.R.D, I.C.A.F.E and U.N.O who publish regular and occasional reports on economic and statistical matters.

(b) Official Publications of Central and State Governments: Several departments of the Central and State Governments regularly publish reports on a number of subjects. They gather additional information. Some of the important publications are: The Reserve Bank of India Bulletin, Census of India, Statistical Abstracts of States, Agricultural Statistics of India, Indian Trade Journal, etc.

(c) Semi-Official Publications: Semi-Government institutions like Municipal Corporations, District Boards, Panchayats, etc. Publish reports relating to different matters of public concern.

(d) Publications of Research Institutions: Indian Statistical Institute (I.S.I), Indian Council of Agricultural Research (I.C.A.R), Indian Agricultural Statistics Research Institute (I.A.S.R.I), etc. Publish the findings of their research programmes.

(e) Publications of various Commercial and Financial Institutions

(f) Reports of various Committees and Commissions appointed by the Government as the Raj Committee’s Report on Agricultural Taxation, Wanchoo Committee’s Report on Taxation and Black Money, etc. are also important sources of secondary data.

(g) Journals and News Papers: Journals and News Papers are very important and powerful source of secondary data. Current and important materials on statistics and socio-economic problems can be obtained from journals and newspapers like Economic Times, Commerce, Capital, Indian Finance, Monthly Statistics of trade etc.

2. Unpublished Sources: Unpublished data can be obtained from many unpublished sources like records maintained by various government and private offices, the theses of the numerous research scholars in the universities or institutions etc.

The choice of data collection methods depends on the facilities available, the degree of accuracy required, the expertise of the researcher, the time span of the study, and other costs and resources associated with and available for data gathering.

Q.10 Discuss the nature and usefulness of a ‘questionnaire’ used for research studies? Also explain the guidelines to be consider while drafting a questionnaire?

Ans. INTRODUCTION

A questionnaire is a pre-formulated written set of questions to which respondents record their answers, usually within rather closely defined alternatives. Questionnaires are an efficient data collection mechanism when the researcher knows exactly what is required and how to measure the variables of interest. Questionnaires can be administered personally, mailed to the respondents, or electronically distributed.

When the survey is confined to a local area, and the organization is willing and able to assemble groups of employees to respond to the questionnaires at the workplace, a good way to collect data is to personally administer the questionnaires. The main advantage of this is that the researcher or a member of the research team can collect all the completed responses within a short period of time. Any doubts that the respondents might have on any question could be clarified on the spot. The researcher is also afforded the opportunity to introduce the research topic and motivate the respondents to offer their frank answers. Administering questionnaires to large numbers of individuals at the same time is less expensive and consumes less time than interviewing; it does not also require as much skill to administer the questionnaire as to conduct interviews. Wherever possible, questionnaires are best administered personally to groups of people because of these advantages. However, organizations are often unable or disinclined to allow work hours to be spent on data collection, and other ways of getting the questionnaires back after completion may have to be found. In such cases, employees may be given blank questionnaires to be collected from them personally on completion after a few days, or mailed back by a certain data in collecting primary data, particularly in surveys and descriptive researches.

The main advantage of mail questionnaires is that a wide geographical area can be covered in the survey. They are mailed to the respondents, who can complete them at their convenience, in their homes, and at their own pace. However, the return rates of mail questionnaires are typically low. A 30% response rate is considered acceptable. Another disadvantage of the mail questionnaire is that any doubts the respondents might have cannot be clarified. Also, with very low return rates it is difficult to establish the representativeness of the sample because those responding to the survey may not at all represent the population they are supposed to. However, some effective techniques can be employed for improving the rates of response to mail questionnaires. Sending follow-up letters, enclosing some small monetary amounts as incentives with the questionnaire, providing the respondent with self-addressed, stamped return envelopes, and keeping the questionnaire brief do indeed help.

Mail questionnaires are also expected to meet with a better response rate when respondents are notified in advance about the forthcoming survey, and a reputed research organization administers them with its own introductory cover letter.

The choice of using the questionnaire as a data gathering method might be restricted if the researcher has to reach subjects with very little education. Adding pictures to the questionnaires, if feasible, might be of help in such cases. For most organizational research, however, after the variables for the research have been identified and the measuires therefore found or developed, the questionnaire is a convenient data collection mechanism. Field studies, comparative surveys, and experimental designs often use questionnaires to measure the variables of interest. Because questionnaires are in common use in surveys, it is necessary to know how to design them effectively. A set of guidelines for questionnaire construction follows.

Objectives of Questionnaire

Any questionnaire has three specific objectives. First, it must translate the information needed into a set of specific questions that the respondents can and will answer. Developing questions that respondents can and will answer and that will yield the desired information is difficult. Two apparently similar ways of posing a question may yield different information. Hence, this objective is a challenge.

Second, a questionnaire must uplift, motivate and encourage the respondent to become involved in the interview, to cooperate, and to complete the interviews. Incomplete interviews have limited usefulness at best. In designing a questionnaire, the researcher should strive to minimize respondent fatigue, boredom, and efforts to minimize incompleteness and non-response.

Third, a questionnaire should minimize response error. The response error may be defined as the error that arises when respondents give inaccurate answers or their answers are misrecorded or misanalyzed. A questionnaire can be major source of response error. Minimizing this error is an important objective of questionnaire design.

QUESTIONNAIRE DESIGN PROCESS

This presents guidelines useful to beginning researchers in designing questionnaires. Although these rules can help you avoid major mistakes, the fine-tuning of a questionnaire comes from the creativity of a skilled researcher.

Questionnaire design will be presented as a series of steps. We will present guidelines for each step. For example, the researcher may discover that respondents misunderstand all the possible workings of question. This may require a loop back to the earlier step of deciding on the question structure.

Specify the information needed: The first step in questionnaire design is to specify the information needed. This is also the first step in the research design process. Note that as the research project progresses, the information needed becomes more and more clearly defined. It is helpful to review components of the problem and the approach, particularly the research questions, hypotheses, and characteristics that influence the research design. To further ensure that the information obtained fully addresses all the components of the problem, the researcher should prepare a set of dummy tables. A dummy table is a blank table used to catalogue data. It describes how the analysis will be structured one the date have been collected.

Specify the Information Needed

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Specify the Type of Interviewing Method

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Determine the Content of Individual questions

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Design the questions to overcome the Respondent’s Inability and Unwillingness to Answer

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Decide on the question structure

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Determine the question wording

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Arrange the question in proper order

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Appearance or “getup”

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Eliminate Bugs by protesting

It is also important to have a clear idea of the target population. The characteristics of the respondent group have a great influence on questionnaire design. Questions that are appropriate for college students may not be appropriate for housewives. Understanding is associated with a high incidence of uncertain or no opinion responses. The more diversified the respondent group, the more difficult it is to design a single questionnaire that is appropriate for the entire group.

Type of interviewing method: An appreciation of how the type of interviewing method influences questionnaire design can be obtained by considering how the questionnaire is administered under each method. In personal interviews, respondents see the questionnaire and interact face-to-face with the interviewer. Thus lengthy, complex, and varied questions can be asked. In telephone interviews, the respondents interact with the interviewer, but they do not see the questionnaire. This limits the type of questions that can be asked to short and simple ones (see the department store patronage project). Mail questionnaires are-administered, so the questions must be simple and detailed instructions must be provided. In computer assisted interviewing (CAPI and CATI), complex skip patterns and randomization of questions to eliminate order bias can be easily accommodated. Internet questionnaires share many of the characteristics of CAPI, but e-mail questionnaires have to be simpler. Questionnaires designed for personal and telephone interviews should be written in a conversational style.

Sketch out the precautions that must be taken while drafting a questionnaire.

A questionnaire is formal set of questions or statements designed to gather information from respondents that will accomplish the goals of the research project. Questionnaires measure people’s attitudes, behavior and feelings toward just about everything.

Factors to be looked into while framing questionnaires:

1.      Shared Vocabulary:

·         Interactive language to be kept simple & understandable

·         Highly technical language should be avoided as much as possible

·         Words used should not be ambiguous or vague.

2.      Unsupported Assumptions: Assumptions should be explicitly stated not implied.

Unsupported assumptions lead to exaggerated estimates.

3.      Frame of Reference: A single word can have several connotations under different situations. The frame of desirability should be made clear.

4.      Biased Wording: Biased Wording should be avoided. Awareness of desirable response leads to shift of focus from actual response.

5.      Adequate Alternatives: Every question should have ample number of alternatives. They should be explicit rather than being implicit.

6.      Double barreled questions: A single question that asks for two responses. Interpretation of the responses not effective.

7.      Positively & negatively worded questions: Respondents are often guided by the directions of the questions. Responses are different when surveys are either exclusively positive or negative. Combination of both is desirable.

8.      Generalizations & Estimates: Proper structuring of questions to avoid generalizations. Answers which require calculations should be avoided.

Q11. What are the different approaches to interview as a method of data collection? Explain their relative merits and demerits.

The interview method of collecting data involves presentation of oral‐verbal stimuli and reply in terms of oral‐verbal responses. This method can be used through:

1. Personal interviews and, if possible, through

2. Telephone interviews

1. Personal Interview: This method requires a person known as the interviewer asking questions generally in a face to face contact to the other person or persons. This sort of interview may be in the form of direct personal investigation or it may be indirect oral investigation. Former method is suitable for extensive investigations. Latter method is used by the commissions and committees appointed by government to carry on investigations.

Advantages:

􀁹 More information and that too in greater depth can be obtained

􀁹 Interviewer by his own skill can overcome the resistance if any

􀁹 There is a greater flexibility in this method

􀁹 Personal information can as well be obtained easily

Disadvantages:

􀁹 it is very expensive method

􀁹 there remains the possibility of the bias of the interviewer

􀁹 This method is relatively more time consuming

􀁹 the presence of the interviewer on the spot may over – stimulate the respondent

2. Telephone interview: This method of collecting information consists in contacting respondents on telephone itself. It is not very widely used method, but plays important part in industrial survey. This method of data collection is quite popular, particularly in case of big enquiries. It is being adopted by the private individuals, research workers, private and public organisations and even by governments. In this method a questionnaire is sent to the persons concerned with the request to answer the questions and return the questionnaire

Advantages:

• Flexible compare to mailing method

• Faster than other methods

• Cheaper than personal interview method

• Call backs are simple and economical also

• High response than mailing method

• Replies can be recorded without embarrassment to respondents

• Interviewer can explain requirements more easily

• No field staff is required

• Wider distribution of sample is possible

Disadvantages:

• Little time is given to respondents

• Survey is restricted to respondents who have telephones

• Not suitable for intensive survey where comprehensive answers are required

• Bias information may be more

• Very difficult to make questionnaire because it should short and to the point

Q12. What are the various kinds of charts and diagrams which are used in data analysis? Distinguish between line chart, bar chart and histogram.

Ans. Graphs are pictorial representations of the relationships between two (or more) variables and are an important part of descriptive statistics. Different types of graphs can be used for illustration purposes depending on the type of variable (nominal, ordinal, or interval) and the issues of interest. The various types of graphs are:

Line Graph: Line graphs use a single line to connect plotted points of interval and, at times, nominal data. Since they are most commonly used to visually represent trends over time, they are sometimes referred to as time-series charts.

Advantages - Line graphs can clarify patterns and trends over time better than most other graphs be visually simpler than bar graphs or histograms summarize a large data set in visual form become more smooth as data points and categories are added be easily understood due to widespread use in business and the media require minimal additional written or verbal explanation.

Disadvantages - Line graphs can be inadequate to describe the attribute, behavior, or condition of interest fail to reveal key assumptions, norms, or causes in the data be easily manipulated to yield false impressions reveal little about key descriptive statistics, skew, or kurtosis fail to provide a check of the accuracy or reasonableness of calculations

Bar graphs are commonly used to show the number or proportion of nominal or ordinal data which possess a particular attribute. They depict the frequency of each category of data points as a bar rising vertically from the horizontal axis. Bar graphs most often represent the number of observations in a given category, such as the number of people in a sample falling into a given income or ethnic group. They can be used to show the proportion of such data points, but the pie chart is more commonly used for this purpose. Bar graphs are especially good for showing how nominal data change over time.

Advantages - Bar graphs can show each nominal or ordinal category in a frequency distribution display relative numbers or proportions of multiple categories summarize a large data set in visual form clarify trends better than do tables or arrays estimate key values at a glance permit a visual check of the accuracy and reasonableness of calculations be easily understood due to widespread use in business and the media

Disadvantages - Bar graphs can require additional written or verbal explanation be easily manipulated to yield false impressions be inadequate to describe the attribute, behavior, or condition of interest fail to reveal key assumptions, norms, causes, effects, or patterns

Histograms are the preferred method for graphing grouped interval data. They depict the number or proportion of data points falling into a given class. For example, a histogram would be appropriate for depicting the number of people in a sample aged 18-35, 36-60, and over 65. While both bar graphs and histograms use bars rising vertically from the horizontal axis, histograms depict continuous classes of data rather than the discrete categories found in bar charts. Thus, there should be no space between the bars of a histogram.

Advantages - Histograms can begin to show the central tendency and dispersion of a data set

closely resemble the bell curve if sufficient data and classes are used show each interval in the frequency distribution summarize a large data set in visual form clarify trends better than do tables or arrays estimate key values at a glance permit a visual check of the accuracy and reasonableness of calculations be easily understood due to widespread use in business and the media use bars whose areas reflect the proportion of data points in each class

Disadvantages - Histograms can require additional written or verbal explanation be easily manipulated to yield false impressions be inadequate to describe the attribute, behavior, or condition of interest fail to reveal key assumptions, norms, causes, effects, or pattern.

Q.13. What do you mean by hypothesis? Explain in detail the procedure of testing a hypothesis?

Hypothesis:

“Hypothesis may be defined as a proposition or a set of propositions set forth as an explanation for the occurrence of some specified group of phenomena either asserted merely as a provisional conjecture to guide some investigation in the light of established facts” (Kothari, 1988). A research hypothesis is quite often a predictive statement, which is capable of being tested using scientific methods that involve an independent and some dependent variables. For instance, the following statements may be considered:

i. “Students who take tuitions perform better than the others who do not receive tuitions” or,

ii. “The female students perform as well as the male students”.

These two statements are hypotheses that can be objectively verified and tested. Thus, they indicate that a hypothesis states what one is looking for. Besides, it is a proposition that can be put to test in order to examine its validity.

Characteristics of Hypothesis:

A hypothesis should have the following characteristic features:-

i. A hypothesis must be precise and clear. If it is not precise and clear, then the inferences drawn on its basis would not be reliable.

ii. A hypothesis must be capable of being put to test. Quite often, the research programmes fail owing to its incapability of being subject to testing for validity. Therefore, some prior study may be conducted by the researcher in order to make a hypothesis testable. A hypothesis “is tested if other deductions can be made from it, which in turn can be confirmed or disproved by observation”.

iii. A hypothesis must state relationship between two variables, in the case of relational hypotheses.

iv. A hypothesis must be specific and limited in scope. This is because a simpler hypothesis generally would be easier to test for the researcher. And therefore, he/she must formulate such hypotheses.

v. As far as possible, a hypothesis must be stated in the simplest language, so as to make it understood by all concerned. However, it should be noted that simplicity of a hypothesis is not related to its significance.

vi. A hypothesis must be consistent and derived from the most known facts. In other words, it should be consistent with a substantial body of established facts. That is, it must be in the form of a statement which is most likely to occur.

vii. A hypothesis must be amenable to testing within a stipulated or reasonable period of time. No matter how excellent a hypothesis, a researcher should not use it if it cannot be tested within a given period of time, as no one can afford to spend a life-time on collecting data to test it.

viii. A hypothesis should state the facts that give rise to the necessity of looking for an explanation. This is to say that by using the hypothesis, and other known and accepted generalizations, a researcher must be able to derive the original problem condition. Therefore, a hypothesis should explain what it actually wants to explain, and for this it should also have an empirical reference.

Concepts Relating to Testing of Hypotheses:

Testing of hypotheses requires a researcher to be familiar with various concepts concerned with it such as:

1) Null Hypothesis and Alternative Hypothesis:

In the context of statistical analysis, hypotheses are of two types viz., null hypothesis and alternative hypothesis. When two methods A and B are compared on their relative superiority, and it is assumed that both the methods are equally good, then such a statement is called as the null hypothesis. On the other hand, if method A is considered relatively superior to method B, or vice-versa, then such a statement is known as an alternative hypothesis. The null hypothesis is expressed as H0, while the alternative hypothesis is expressed as Ha. For example, if a researcher wants to test the hypothesis that the population mean (μ) is equal to the hypothesized mean (H0) = 100, then the null hypothesis should be stated as the population mean is equal to the hypothesized mean 100. Symbolically it may be written as:-

H0: = μ = μ H0 = 100

If sample results do not support this null hypothesis, then it should be concluded that something else is true. The conclusion of rejecting the null hypothesis is called as alternative hypothesis H1. To put it in simple words, the set of alternatives to the null hypothesis is termed as the alternative hypothesis. If H0 is accepted, then it implies that Ha is being rejected. On the other hand, if H0 is rejected, it means that Ha is being accepted. For H0: μ = μ H0 = 100, the following three possible alternative hypotheses may be considered:29

Alternative hypothesis	To be read as follows
H1: μ ≠ μ H0	The alternative hypothesis is that the population mean is not equal to 100, i.e., it could be greater than or less than 100
H1 : μ > μ H0	The alternative hypothesis is that the population mean is greater than 100
H1 : μ < μ H0	The alternative hypothesis is that the population mean is less than 100

Before the sample is drawn, the researcher has to state the null hypothesis and the alternative hypothesis. While formulating the null hypothesis, the following aspects need to be considered:

A. Alternative hypothesis is usually the one which a researcher wishes to prove, whereas the null hypothesis is the one which he/she wishes to disprove. Thus, a null hypothesis is usually the one which a researcher tries to reject, while an alternative hypothesis is the one that represents all other possibilities.

B. The rejection of a hypothesis when it is actually true involves great risk, as it indicates that it is a null hypothesis because then the probability of rejecting it when it is true is α (i.e., the level of significance) which is chosen very small.

C. Null hypothesis should always be specific hypothesis i.e., it should not state about or approximately a certain value.

2) The Level Of Significance:

In the context of hypothesis testing, the level of significance is a very important concept. It is a certain percentage that should be chosen with great care, reason and insight. If for instance, the significance level is taken at 5 per cent, then it means that H0 would be rejected when the sampling result has a less than 0.05 probability of occurrence when H0 is true. In other words, the five per cent level of significance implies that the researcher is willing to take a risk of five per cent of rejecting the null hypothesis, when (H0) is actually true. In sum, the significance level reflects the maximum value of the probability of rejecting H0 when it is actually true, and which is usually determined prior to testing the hypothesis.

3) Test of Hypothesis or Decision Rule:

Suppose the given hypothesis is H0 and the alternative hypothesis H1, then the researcher has to make a rule known as the decision rule. According to the decision rule, the researcher accepts or rejects H0. For example, if the H0 is that certain students are good against the H1 that all the students are good, then the researcher should decide the number of items to be tested and the criteria on the basis of which to accept or reject the hypothesis.

4) Type I and Type II Errors:

As regards the testing of hypotheses, a researcher can make basically two types of errors. He/she may reject H0 when it is true, or accept H0 when it is not true. The former is called as Type I error and the latter is known as Type II error. In other words, Type I error implies the rejection of a hypothesis when it must have been accepted, while Type II error implies the acceptance of a hypothesis which must have been rejected. Type I error is denoted by α (alpha) and is known as α error, while Type II error is usually denoted by β (beta) and is known as β error.

5) One-Tailed and Two-Tailed Tests:

These two types of tests are very important in the context of hypothesis testing. A two-tailed test rejects the null hypothesis, when the sample mean is significantly greater or lower than the hypothesized value of the mean of the population. Such a test is suitable when the null hypothesis is some specified value; the alternative hypothesis is a value that is not equal to the specified value of the null hypothesis.

 

 

Procedure of Hypothesis Testing:

 

Testing a hypothesis refers to verifying whether the hypothesis is valid or not. Hypothesis testing attempts to check whether to accept or not to accept the null hypothesis. The procedure of hypothesis testing includes all the steps that a researcher undertakes for making a choice between the two alternative actions of rejecting or accepting a null hypothesis. The various steps involved in hypothesis testing are as follows:

1) Making a Formal Statement: This step involves making a formal statement of the null hypothesis (H0) and the alternative hypothesis (Ha). This implies that the hypotheses should be clearly stated within the purview of the research problem. For example, suppose a school teacher wants to test the understanding capacity of the students which must be rated more than 90 per cent in terms of marks, the hypotheses may be stated as follows:

Null Hypothesis H0 : = 100 Alternative Hypothesis H1 : > 100

2) Selecting a Significance Level:

The hypotheses should be tested on a pre-determined level of significance, which should be specified. Usually, either 5% level or 1% level is considered for the purpose. The factors that determine the levels of significance are: (a) the magnitude of difference between the sample means; (b) the sample size: (c) the variability of measurements within samples; and (d) whether the hypothesis is directional or non-directional. In sum, the level of significance should be sufficient in the context of the nature and purpose of enquiry.

3) Deciding the Distribution to Use:

After making decision on the level of significance for hypothesis testing, the researcher has to next determine the appropriate sampling distribution. The choice to be made generally relates to normal distribution and the t-distribution. The rules governing the selection of the correct distribution are similar to the ones already discussed with respect to estimation.

4) Selection of a Random Sample and Computing An Appropriate Value:

Another step involved in hypothesis testing is the selection of a random sample and then computing a suitable value from the sample data relating to test statistic by using the appropriate distribution. In other words, it involves drawing a sample for furnishing empirical data.

5) Calculation of the Probability:

The next step for the researcher is to calculate the probability that the sample result would diverge as far as it can from expectations, under the situation when the null hypothesis is actually true.

6) Comparing the Probability:

Another step involved consists of making a comparison of the probability calculated with the specified value of α, i.e. The significance level. If the calculated probability works out to be equal to or smaller than the α value in case of one-tailed test, then the null hypothesis is to be rejected. On the other hand, if the calculated probability is greater, then the null hypothesis is to be accepted. In case the null hypothesis H0 is rejected, the researcher runs the risk of committing the Type I error. But, if the null hypothesis H0 is accepted, then it involves some risk (which cannot be specified in size as long as H0 is vague and not specific) of committing the Type II error.

Q.14 What is t-distribution? What are the uses of t-test in research decision making?

Ans. A t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution under the null hypothesis. It can be used to determine if two sets of data are significantly different from each other.

A t-test is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known. When the scaling term is unknown and is replaced by an estimate based on the data, the test statistics (under certain conditions) follow a Student's t distribution.

Among the most frequently used t-tests are:

·         A one-sample location test of whether the mean of a population has a value specified in a null hypothesis.

·         A two-sample location test of the null hypothesis such that the means of two populations are equal. All such tests are usually called Student's t-tests, though strictly speaking that name should only be used if the variances of the two populations are also assumed to be equal; the form of the test used when this assumption is dropped is sometimes called Welch's t-test. These tests are often referred to as "unpaired" or "independent samples" t-tests, as they are typically applied when the statistical units underlying the two samples being compared are non-overlapping.

·         A test of the null hypothesis that the difference between two responses measured on the same statistical unit has a mean value of zero. For example, suppose we measure the size of a cancer patient's tum or before and after a treatment. If the treatment is effective, we expect the tum or size for many of the patients to be smaller following the treatment. This is often referred to as the "paired" or "repeated measures" t-test: see paired difference test.

·         A test of whether the slope of a regression line differs significantly from 0.

 

Q.15. Write a short note on:

(a) Z-test

(b) Chi-square test

Ans. Z-test

A Z-test is a type of hypothesis test. Hypothesis testing is just a way for you to figure out if results from a test are valid or repeatable. For example, if someone said they had found a new drug that cures cancer, you would want to be sure it was probably true. A hypothesis test will tell you if it’s probably true, or probably not true. A Z test, is used when your data is approximately normally distributed.

Several different types of tests are used in statistics (i.e. f test, chi square test, t test). You would use a Z test if:

·         Your sample size is greater than 30. Otherwise, use a t test.

·         Data points should be independent from each other. In other words, one data point isn’t related or doesn’t affect another data point.

·         Your data should be normally distributed. However, for large sample sizes (over 30) this doesn’t always matter.

·         Your data should be randomly selected from a population, where each item has an equal chance of being selected.

·         Sample sizes should be equal if at all possible.

Running a Z test on your data requires five steps:

1.      State the null hypothesis and alternate hypothesis.

2.      Choose an alpha level.

3.      Find the critical value of z in a z table.

4.      Calculate the z test statistic (see below).

5.      Compare the test statistic to the critical z value and decide if you should support or reject the null hypothesis.

F-TEST

F-tests are named after its test statistic, F, which was named in honor of Sir Ronald Fisher. The F-statistic is simply a ratio of two variances. Variances are a measure of dispersion, or how far the data are scattered from the mean. Larger values represent greater dispersion.

Variance is the square of the standard deviation. For us humans, standard deviations are easier to understand than variances because they’re in the same units as the data rather than squared units. However, many analyses actually use variances in the calculations.

F-statistics are based on the ratio of mean squares. The term “mean squares” may sound confusing but it is simply an estimate of population variance that accounts for the degrees of freedom (DF) used to calculate that estimate.

Despite being a ratio of variances, you can use F-tests in a wide variety of situations. Unsurprisingly, the F-test can assess the equality of variances. However, by changing the variances that are included in the ratio, the F-test becomes a very flexible test. For example, you can use F-statistics and F-tests to test the overall significance for a regression model, to compare the fits of different models, to test specific regression terms, and to test the equality of means.


UNIT IV

RESEARCH REPORT
INTRODUCTION 
Research reporting is the oral or written presentation of evidence and the findings in such a way that it is readily understood and assessed by the reader and enables him to verify the validity of the conclusions. Research report writing is the culmination of the research investigation. It is at the stage of reporting that the researcher assembles the findings of the study, draws conclusions and evaluates his own findings. Report writing is the end product of research activity. It is highly skilled work; it is an interesting, fascinating, challenging, gruelling and sometimes even exasperating experience. Writing a research report is a technical activity that demands all the skills and patience of the researcher. It requires considerable thought, effort, patience and penetration and an overall approach to the problem, data and analysis. Also needed is firm control over language and great objectivity. A vast amount of planning and preparation is necessary for organising and writing the report. Perfection in a research report is achieved by continuous and persistent thought and creative and intelligent writing. Only hard and patient work on the facts, careful and critical assessment and intelligent planning in organising the report can facilitate communication. There are no standard criteria for the organisation of a report, popular or technical. They depend on each investigation, problem, the novelty or familiarity of the methods, nature and volume of facts, techniques of analysis and so on.

No research project is complete without a report. The nature of the report is determined by the project itself and to whom it is addressed. Academic research is expected to produce lengthy reports, or theses, covering all aspects of the research and reporting on them in a precise and rather formal manner. But no matter what the size or formality of the report, it is reasonable to expect it to convey information on a fairly standard set of topics. First, it must say why the work was done, what events led up to it and what other work was found to be relevant. This is usually contained in the introduction, which should also include the precise statement of the objective and aims of the project.
Generally, there should be a section describing what work was done. This should cover the methods used, their selection and any problems experienced in their application. From this it is easy to move on to what was found out, or the results. In turn, these lead on to the conclusions, which are a statement of what the researcher deduced from the results, and then on to the recommendations, which set out what the researcher feels should be the action taken as a result of the conclusions. Writing is not an activity that can be allocated an odd half-hour whenever it is convenient. It requires sustained concentration. The amount of time needed to make real progress in your writing depends on the way you prefer to work. Most people find that it takes a day to write about 2,000 words. But we all work in different ways. Some people, once they get started, prefer to continue until they drop from exhaustion! Others like to set a strict timetable, devoting three or four hours a day to writing. Whichever category you fall into, make sure you have time for writing allocated in your diary. We have found that it is helpful to have blocks of time where writing can take place on successive days. This ensures a degree of continuity of ideas, which isn’t easy to maintain if you keep having to ‘think your way back’ into your research.

 TYPES OF REPORTS 
Research reports may differ in length and form. Generally, business firms prefer reports in the form of letters. Banks, insurance companies and financial institutions require short balance-sheet type of tabulation in their annual reports to customers and shareholders. The results of a research investigation can be presented in a number of ways: as a technical report, a popular report, an article, a monograph or at times even in the form of an oral presentation. A technical report is used whenever a full written report of the study is required whether for record keeping or for public dissemination. A popular report is used if the research results have policy implications.
A. Technical report
A technical report is written for fellow researchers and therefore should be organised on a different footing altogether. In such a report, the researcher is expected to give a full account of the technical aspects, both in the sampling methods and the subject matter. Fellow professionals are more concerned about the methods employed. In fact, the value of the findings depends on the techniques adopted. The conceptual and analytical framework sample design should be adequately explained. A technical report consists of the following aspects.
1. Major findings and contents: A technical report will contain the main findings just in two or three pages.
2. Nature of the research work: This describes the general objectives of the study, formulation of the problem in operational items, the working hypothesis, the type of analysis, data required, etc.
3. Research methodology: This explains the various methods used in the study and their limitations. For instance, sample size, sample selection, etc.
4. Data analysis: The report analyses the data and their sources, characteristics and limitations. If secondary data are used, their suitability to the problem at hand is fully assessed. In case of a survey, the manner in which data were collected should be fully described.
5. Presentation of findings: The researcher presents his main findings of the study with supporting data in the form of tables and charts. This part is the main body of the report, usually extending over several chapters.
6. Main conclusion: Here, the main findings of the research are presented and the main body of the report, usually extending over several chapters.
7. Bibliography: This contains the main sources of secondary data.
8. Technical appendices: These contain all technical matters relating to questionnaires, mathematical derivations, elaboration on particular techniques of analysis and the like.
The above format provides a general idea of the nature of a technical report; the order of presentation may not necessarily be the same in all technical reports. Therefore, the presentation may differ; the different sections outlined above will not always be the same, nor will all these sections appear in any particular report.
 
B. Popular report
This stresses on simplicity and attractiveness. Its writing is clear, with minimum statistical details and the liberal use of charts and diagrams. It has an attractive layout, large print size, many subheadings, and may be even some cartoons. Besides, it emphasises on the practical aspects and policy implications. The following is the general outline of a popular report:
1. Major findings and conclusions: The report will have findings of practical interest and their implications.
2. Follow-up action: It will suggest follow-up action on the basis of the findings of the study in this section.
3. Objectives of the study: Here the problem is presented, along with the specific objectives of the study.
4. Methodology: Here, a description of the methods and techniques used, including a short review of the data on which the study is based, is provided.
5. Results: This is the main body of the report, presented in clear and non-technical terms with the liberal use of all sorts of illustrations such as charts, diagrams and the like.
6. Appendices: This consists of detailed information on the methods used, forms, etc. Appendices are generally not included if the report is meant for the general public.
A popular report emphasises on simplicity and policy implications from the operational point of view, avoiding technical details.
The following outline may be adopted while preparing the research report:

(I) The preliminaries Title page. Preface or foreword, acknowledgements. Graphs or illustrations, tables, charts. Table of contents.
(II) Contents of the report:
1. Introduction Objectives of the study, statement of the problem, hypotheses and definition of concepts. Review of literature and research studies. Time, place and materials of the survey. Scope, assumptions and limitations. Organisation and sampling procedures. Methods, tools and techniques employed for data collection.
2. Analysis and presentation of results: Report of facts— nature, volume and dimension. Statistical analysis of data. Summary of findings and recommendations.
3. The reference materials: Bibliography. Appendices— questionnaires/statistical tables etc. Glossary of terms Index

PHYSICAL LAYOUT OF THE REPORT
The manuscript should be typed or printed on unruled white paper, leaving one-and-a-half-inch margins on both the right and left sides (lateral sides) of the paper. There should also be a one-inch margin, top and bottom (vertical margin/header and footer). The paper should be neat, legible and printed in double-spaced lines preferably in the Times New Roman font with 12 point letter size. The physical arrangement of the paper gives a better appearance, which elicits more interest among readers.
PLANNING AND ORGANISATION OF AN ACADEMIC REPORT
Proper planning and organisation of study materials are important while preparing the research report. At the writing stage, a researcher will have accumulated a mass of data and information that will have to be prudently and carefully used. Well-conceived planning and organisation facilitates the writing of the report, with a proper emphasis on the different aspects of the study. Planning involves each chapter and aspect of the report. It is nothing but the arrangement of ideas in a logical and coherent manner within the framework of the overall structure laid down.

Stages of writing an academic report
In general, there are six stages in writing a report. They are: • Systematic analysis of the subject. • Drawing the outline of the report. • Preparation of the rough draft. • Enrichment of the final draft. • Preparation of the final bibliography. • Finalising the complete draft.
Now we will discuss some of the important stages:
(a) Finalising the complete draft: This is the first step in writing a report. The final draft should be written in simple language and in a concise and condensed form. The researcher must avoid vague
expressions such as ‘it seems’, ‘may be’ and ‘could be’, abstract terminology and technical jargon. At the outset, the report should reflect the study’s intention to solve some intellectual problem and adding to the knowledge of both the researcher and the reader. At the same time, it should be written in such a way that it attracts the readers’ interest and shows some originality in presentation. Some researchers may incorporate the current trends in the field, common experiences, critical incidents etc. to strengthen and reinforce the findings of the research.
(b) Formation of an outline: An outline is a must while writing a report; it is like the skeleton in a human body. The outline of the study is made at two stages: once at the beginning of the study, which serves as a design of the study, and once before writing the report. The outline prepared for writing the report should be elaborate so as to include all important aspects that should find a place in the report. The outline should be prepared at three stages: topical outline, paragraph outline and sentence outline.
Topical outline: This includes the chapters and broad aspects to be included in each chapter. It is a skeleton outline.
Paragraph outline: This includes all major paragraphs, indicating the central idea of each paragraph.
Sentence outline: This does not imply writing of sentences. It merely involves points to be covered in sentences.
The following points need to be observed while planning an outline:
• It should be as detailed as possible and should enable continuous writing.
• It should not be vague and should not include such value phrases as ‘body’, ‘facts and figures’, etc, which give no direction to the report writing.
• It should fulfil the considerations of chronology, topical unity, coherence and transition.
• Each paragraph should contain one major idea.
(c) Important parts of a report
1. The preliminaries: The following aspects should be highlighted in the first part of the research report: • Title of the report. • Acknowledgement • Preface • Foreword • Contents • List of tables and illustrations
2. The abstract: This is probably the most important part of the report because it may be the only part that some will read. It is a short summary of the complete project report. This enables those who are not sure whether they wish to read the complete report to make an informed decision. For those who intend to read the whole report, the abstract prepares them for what is to come. An abstract should contain four short paragraphs with the answers to the following questions:
• What are my research questions and why are they important?
• How did I go about answering the research question(s)?
• What did I find out?
• What conclusions do I draw regarding my research question(s)?
Smith (1991) lists five characteristics of a good abstract:
• It should be short. Try to keep it to a maximum of two sides of an A4-size paper sheet.
• It must be self-contained. Since it may be the only part of your report that some people see, it follows that it must summarise the complete content of your report.
• It must satisfy your reader’s needs. Your reader must be told about the problem or central issue that the research addresses and the method adopted to solve it. It must also contain a brief statement of the main results and conclusions.
• It must have the same emphasis as the report, with the consequence that the reader should gain an accurate impression of the report’s  content from the abstract.
• It should be objective, precise and easy to read. The project report contents page should give you the outline structure for the abstract. Summarising each section should give you an accurate resume of the content of the report. Do ensure that you stick to what you have written in the report. The abstract is not the place for elaborating any of your main themes. Be objective. You will need to write several drafts before you eliminate every word that is not absolutely necessary. The purpose is to convey the content of your report in as clear and brief a way as possible.
• Writing a good abstract is difficult. The obvious thing to do is to write it after you have finished the report. We suggest that you draft it when you start writing the report so that your storyline is abundantly clear in your mind. You can then amend the draft when you have finished the report so that it conforms to the five principles above.

3. Research design: The researcher should highlight the research design of the project. The researcher should answer the following questions: 
• What is its basic design? • What are the methods adopted to collect data? • How is the study carried out? • Is it an experimental/survey/historical data research method? • If the study is an experimental one, what are the experimental manipulations? • What type of questionnaire/interview/observations is used? • If measurements were based on observation, what instructions are given to the observers? • Who are the subjects? • How many of them have been selected? • How have they been selected? • How have they been selected? • Are the research instruments reliable? • Do the research instruments have validity?
All these questions, when properly answered, can be used to estimate the probable limits of the findings’ generalisability. The researcher has to take proper care to develop a well-planned research design, which is free from errors and limitations. To ensure the reliability and validity of the tools and instruments, a pilot study can be conducted to verify its strengths and utility.

4. Analysis of data: Here, the researcher has to highlight the type of statistical analysis adopted to analyse the data. The analysis can be listed from simple descriptive analysis to complex multivariate analysis.

5. The results: Once the analysis is over, the results can be depicted in a tabulated form, with appropriate illustrations. A detailed presentation of the findings of the study is a major part of the research report. These can be supported in the form of tables and charts together with a validation of results. Since it comprises the main body of the report, it generally extends over several chapters. It is advisable to project summarised results rather than raw data. All the results should be presented in logical sequence and split into readily identifiable sections. All relevant results must find a place in the report. All the results of the report should address the research problems stated earlier in the report, illustrating whether the results support or reject the hypothesis. But ultimately the researcher must rely on his own judgement in deciding the outline of his report.

Interpretation of results— some hints • To find the relationships among the variables that are studied and observing the commonality, uniqueness, diversity etc. among them. • To observe the role of extraneous variables. How they affect the various phenomena studied. • To ensure validity; the results can be cross-checked with others through consultation. • To consider all the relevant factors affecting the problem before generalising it to the whole population.
The prime tasks of interpretation is to bring to the surface the gist of the findings. A researcher should explain why the findings are so, in objective terms. He should try to bring out the principles involved in the observations. He can also make reasonable prediction. On the basis of interpretation of an exploratory study, a new hypothesis can be formulated for experimental research. During interpretation, unconnected, isolated facts should not be discarded, but should be explained properly. Interpretation leads to the establishment of some explanatory concepts arising out of the connection between the underlying processes and principles, and the observed facts from a working model. A researcher’s task is to identify and disengage such principles and processes. Interpretation can also provide a theoretical conception, which can be the basis of further researcher and new knowledge. Thus, continuity in research can be established and the quest for knowing the unknown can be sustained.
Prerequisites for good interpretation: some guidelines 
— While drawing inferences from the analysis of data, the researcher has to ensure that the inferences are free from any biases and mistakes that may arise due to both subjective and objective factors. This can be minimised by: checking whether (a) the data are appropriate, trustworthy and adequate for drawing inferences b) the data reflect good homogeneity and (c) proper analysis has been done through statistical methods.
— The researcher should also check for personal bias (subjective element) while interpreting the results. There are so many pitfalls that have to be avoided while observing and interpreting the results. Some of them are: stereotyping (conforming with existing results), preoccupation with set results, projecting his own views on the subject, snap judgements, lack of appreciation for others’ feelings, prejudicial treatment and so on. The researcher must remain vigilant about all such things so that false generalisations may not take place. He should be well-equipped with statistical measures and must know their correct use for drawing inferences concerning his study.
— The researcher must always keep in view that the task of interpretation is very much intertwined with analysis and cannot be separated. He should take precautions about the reliability of data, computational checks, validation and comparison of results.
— The researcher should also pay attention to the hidden factors underlying the results. Broad generalisations should be avoided because the coverage may be restricted to a particular time, area and conditions.
— Originality and creativity are critical in interpreting the results. While linking the relationship between theoretical orientation and empirical observation, the researcher has to make use of his originality and creativity in developing concepts and models. He must pay special attention to this aspect while engaged in the task of interpretation.
6. Summary: It is a generally practice to conclude the report with a very brief summary. In business reports, it is called an executive summary. Here, all the aspects of the research report are given in capsule form.
7. Reference material: The listing of reference material comes at the end of any research report. Appendices with all technical data such as questionnaires, sample information, mathematical derivations etc. should be included at the end. The bibliography, listed in alphabetical order, should be added in the last section. Similarly, the researcher has to prepare an index (an alphabetical listing of names, places and topics along with the page numbers in the book or report in which they are mentioned). That should invariably be given at the end of the report.
8. Other considerations:
Use of quotations: The appropriate use of quotations will enrich the effective presentation of research reports. Quotations should be placed within quotation marks and double-spaced. In case the quotation is lengthy, it can be typed in single space and indented at least half an inch to the right of the normal text margin.
Punctuation and abbreviations: The researcher has to take care to check punctuation marks such as commas, full stops, colons, semicolons etc. these punctuation marks can be checked and verified in listing the bibliography, references, citations, documentations etc. For example, in listing the reference, the author’s name is followed by a comma. After the comma, the title of the book is given; the article (such as ‘a’, ‘an’, ‘the’ etc.) is omitted and only the first word, proper nouns and adjectives are capitalised. A comma follows the title. Information concerning the edition is given next. This entry is followed by a comma. The place of publication is then stated; it may be mentioned in an abbreviated form. For example, London is abbreviated as Lond, New York as N.Y. and so on.

REFERENCING IN THE TEXT 
The Harvard system, which we have adopted in this book, uses the author’s name and data of publication to identify cited documents within the text. For example: • It has been shown that… (Saunders, 1993). • When referring generally to work by different authors on the subject, place the authors in alphabetical order: (Baker, 1991; Lewis, 1991; Thornhill, 1993). • When referring to dual authors: (Saunders and Cooper, 1993). • When there are more than two authors: (Bryce et al., 1991). • For corporate authors, for instance a company report: (Hanson Trust Plc, 1990). • For publications with no obvious author; for example an employment gazette: (Employment Gazette, 1993).
• When referring to different publications by the same author, the works should be arranged according to date in ascending order: (Lewis, 1989, 1991). • To differetiate between publications by the same author in the same year use a, b, c etc., (Forster, 1991a). Make sure that this is consistent throughout the research project and corresponds with the bibliography. • To reference an author referred to by another author where the original publication has not been read: (Granovetter, 1974, cited by Saunders, 1993). In this case the author who cites and the original document’s author should both appear in the bibliography.

REFERENCING IN THE BIBLIOGRAPHY
In the bibliography, the referenced publications are listed alphabetically by author’s name. All the author’s surnames and initials are listed in full. If there is more than one work by the same author, these are listed chronologically. • An example of a reference to a book would be: Saunders, M.N.K. and Cooper, S.A., (1993) Understanding Business Statistics, London, DP Publciations. • A reference to a book other than the first edition would be: Morris, C., (1993) Quantitative Approaches to Business Studies (3rd ed.,) London, Pitman Publishing. • A reference to a book with no obvious author would be: Department of Trade and Industry (1992). The Single Market: Europe open for Professions, UK Implementation, London, HMSO. • A reference to a particular chapter in a book would be: Robsoon, C., (1993) Real World Research, Oxford, Blackwell, Chapter 3.

• A reference to a  particular chapter in an edited book would be: Graig, P.B. (1991) ‘Designing and Using Mail Questionnaires’, in Smith, N.C. and Dainty, P. (eds) The Management Research Handbook, London, Routledge, pp. 181-89. • An example of a reference to an article in a journal (in this example  volume 20, part 6 would be): Brewster, C. and Bournois, F., (1992) ‘uman Resource Management: A European Perspective’, Personnel Review, 20: 6, 4-13.

FOOTNOTES
Researchers must insert footnotes in the appropriate places. These fulfil two purposes: • The proper identification of materials used in quotations in the report. • The footnotes provide supplementary value to the main body of the text. Based on the footnotes’ description, one can easily refer the cross references, citation of authorities and sources, acknowledgement and elucidation or explanation of a point of view. The recent trend is to avoid footnotes. Some people feel that they enhance display of the scholarship of the researchers. But it is neither an end nor a means of displaying scholarship.

Referencing in the Text
When using footnotes, a number shows references within the research report. For example: ‘Recent research1 indicates that…’ This number refers directly to the references.

Referencing in the reference
These list the referenced publications sequentially in the order they are referred to in your research report. This can be useful as it enables you to include comments and footnotes as well as references. • The layout of individual references in the bibliography is the same as that for the Harvard system. • If you find that your refer to the same item more than once you can use standard bibliographic abbreviations to save repeating the references in full. • The publications referred to only include those you have cited in your report. They should therefore be headed ‘References’ rather than ‘Bibliography’ as shown below: Abbreviation Explanation Op. cit. (opere ciato) Meaning, in the work cited. This refers to a work previously referenced and so you must give the author and date and if necessary the page number, like: Robson (1993) op. cit. pp. 23-4. Loc. Cit. (loco ciato) Meaning, in the place cited. This refers to the same page of a work previously referenced. So you must give the author and date, like: Robson (1993) loc. Cit. Ibid. (ibidem) Meaning, the same work given immediately before. This refers to the work referenced immediately before and replaces all details of the previous reference other than a page number if necessary.

PRECAUTIONS IN PREPARING REPORT
1. A report is an important way of communicating research findings to others. A good research report is one that does this task efficiently and effectively. Hence, the following precautions must be taken while preparing it: 2. While determining the length of the report, one should keep in mind the fact that it should be long enough to cover the subject but short enough to maintain interest. In fact, report writing should not be a means to learning more and more about less and less. 3. Abstract terminology and technical jargon should be avoided. The report should be able to convey the matter as simply as possible. In other words, this means that reports should be written in an objective style in simple language, avoiding expressions such as ‘it seems’, ‘there may be’ and the like. 4. Readers are often interested in acquiring quick knowledge of the main findings and as such the report must make the findings readily accessible. For this purpose, charts, graphs and statistical tables may be used for the various results in the main report in addition to summaries of important findings. 5. The layout of the research should be well thought out. It must be appropriate and in accordance with the objective of the research problem. 6. The report should be free from grammatical mistakes and must be prepared strictly according to the rules of composition of research reports such as the use of quotation marks, footnotes, documentation, punctuation and use of abbreviations in footnotes and the like.

7. The report must present a logical analysis of the subject matter. It must reflect a structure wherein the different pieces of analysis relating to the research problem fit well. 8. A research report should show originality and should necessarily be an attempt to solve some intellectual problem. It must contribute to the solution of a problem and must add to the store of knowledge. 9. Towards the end, the report must also state the policy implications of the problem under consideration. It is usually considered desirable for a report to make a forecast of the probable future of the subject concerned and indicate the kind of research that still needs to be done in that particular field. 10. Appendices should be enlisted for all the technical data in the report. 11. Bibliography of sources consulted is a must for a good report. 12. An index is also considered an essential part of a good report and as such must be prepared and appended at the end. 13. The report must have an attractive appearance. It should be neat and clean, whether typed or printed. 14. Calculated confidence limits must be mentioned and the various constraints experienced in conducting the research study stated. 15. The objective of the study, the nature of the problem, the methods employed and the technique of analysis adopted must all be stated at the beginning of the report in the form of an introduction.

 EVALUATION OF A REPORT— SOME CONSIDERATIONS
The evaluator has to give a report on the thesis or dissertation evaluated by him. There is no standard format for this report. The evaluator is expected to comment on (1) the importance of the study; (2) soundness of the methodology; (3) quality of analysis; (4) significance of the findings, and (5) format and style of presentation. It is not necessary for him to summarise the contents of the thesis. But he must point out the strengths and weaknesses of the work. He should give his final recommendation— whether the thesis should be accepted or rejected— in clear terms. If the thesis needs revision and re-submission, the evaluator should recommended that these be done. In this case, he should offer specific suggestions for revision.

Evaluation Criteria
There is no universally accepted set of standards for evaluating a research report. However, the following checklist will serve as a general guideline for a critical evaluation or analysis of a research report:
1. The appropriateness of the title
(a) Does it exactly indicate the core of the study? (b) Is it clear and concise? (c) Does it promise no more than what the study can provide?
2. Importance of the problem
(a) Is the research problem topically important? (b) Is it socially relevant in terms of its contribution to knowledge and/or solution to the burning problem of the day? (c) Are the research questions (objectives) clearly stated? (d) Are they specific and related to the selected theme? 
(e) Are the hypotheses pertinent to the research questions? (f) Are they clearly stated and testable? (g) Are the concepts in the title, objectives and hypotheses operationally defined? (h) Are the operational definitions valid and reasonable? (i) Are assumptions and limitations stated? (j) Does the problem formulation reflect the researcher’s mastery of the subject matter of the study?
3. Review of related literature and earlier studies
(a) Is this review covered adequately? (b) Is it well-organised and documented? (c) Has the research gap been identified? (d) Does the present study fill in the gap?
4. Soundness of the methodology:
(a) Are the type of research and sources and methods of data collection described in detail? (b) Are the above methods appropriate to the problem under study and the respondents? (c) Is the research design appropriate to test adequately the hypothesised relationships? (d) Is the sampling design appropriate and described in detail? (e) Are the methods adopted for sampling scientific? (f) Is the sample size adequate? (g) Are relevant variables recognised, defined, inter-related and measured? (h) Are the data-gathering instruments appropriate? (i) Are the validity and reliability of the instruments established? (j) Are the details of the methodology adequate for replicability? 
5. Data analysis
(a) Is the analysis objective and deep? (b) Is the statistical treatment appropriate? (c) Is appropriate use made of tables and charts? (d) Is their format proper and complete? (e) Have the hypotheses been adequately tested? (f) Is the analysis of data relationship logical and perceptive? (g) Is the significance of statistical results tested properly? (h) Are the statistical results interpreted and presented without any bias?
6. Contribution of the study and conclusions and recommendations
(a) Are the findings of the study stated clearly? (b) Are the findings generalisable? (c) Does the study test a theory or develop a new theory, a new model or new tool or contribute to methodology in any other way? (d) Are the conclusions logical and justified by the empirical evidence? (e) Are the implications of the results for policy and action explicitly pointed out? (f) Do the recommendatiosn flow from the findings? (g) Are the recommendatiosn specific and practical?
7. Presentation
(a) Is the format of the report appropriate? (b) Does the report have headings and sub-headings that facilitate reading and understanding it? (c) Is the chapter scheme based on the objective of the study?

(d) Is the textual discussion clear, concise and convincing? (e) Is the style of writing smooth and simple? (f) Is it free from spelling and grammatical errors? (g) Do the footnotes/references contain full details of the sources? (h) Is the bibliography exhaustive?