Description
Methodology is the systematic, theoretical analysis of the methods applied to a field of study, or the theoretical analysis of the body of methods and principles associated with a branch of knowledge.
Master of Business Administration-MBA Semester 3 Research Methodology– MB0050 (Book ID: B1206) Assignment Set- 1
Question 1: How is a research problem formulated? Answer: Formulating the Problem The selection of one appropriate researchable problem out of the identified problems requires evaluation of those alternatives against certain criteria, which may be grouped into: Internal Criteria Internal Criteria consists of: 1) Researcher?s interest: The problem should interest the researcher and be a challenge to him. Without interest and curiosity, he may not develop sustained perseverance. Even a small difficulty may become an excuse for discontinuing the study. Interest in a problem depends upon the researcher?s educational background, experience, outlook and sensitivity. 2) Researcher?s competence: A mere interest in a problem will not do. The researcher must be competent to plan and carry out a study of the problem. He must have the ability to grasp and deal with int. he must possess adequate knowledge of the subject-matter, relevant methodology and statistical procedures. 3) Researcher?s own resource: In the case of a research to be done by a researcher on his own, consideration of his own financial resource is pertinent. If it is beyond his means, he will not be able to complete the work, unless he gets some external financial support. Time resource is more important than finance. Research is a timeconsuming process; hence it should be properly utilized. External Criteria 1) Research-ability of the problem: The problem should be researchable, i.e., amendable for finding answers to the questions involved in it through scientific
method. To be researchable a question must be one for which observation or other data collection in the real world can provide the answer. 2) Importance and urgency: Problems requiring investigation are unlimited, but available research efforts are very much limited. Therefore, in selecting problems for research, their relative importance and significance should be considered. An important and urgent problem should be given priority over an unimportant one. 3) Novelty of the problem: The problem must have novelty. There is no use of wasting one?s time and energy on a problem already studied thoroughly by others. This does not mean that replication is always needless. In social sciences in some cases, it is appropriate to replicate (repeat) a study in order to verify the validity of its findings to a different situation. 4) Feasibility: A problem may be a new one and also important, but if research on it is not feasible, it cannot be selected. Hence feasibility is a very important consideration. 5) Facilities: Research requires certain facilities such as well-equipped library facility, suitable and competent guidance, data analysis facility, etc. Hence the availability of the facilities relevant to the problem must be considered. 6) Usefulness and social relevance: Above all, the study of the problem should make significant contribution to the concerned body of knowledge or to the solution of some significant practical problem. It should be socially relevant. This consideration is particularly important in the case of higher level academic research and sponsored research. 7) Research personnel: Research undertaken by professors and by research organizations require the services of investigators and research officers. But in India and other developing countries, research has not yet become a prospective profession. Hence talent persons are not attracted to research projects. Each identified problem must be evaluated in terms of the above internal and external criteria and the most appropriate one may be selected by a research scholar.
Question 2: What are the characteristics of a good research design? Answer: Characteristics of a Good Research Design
1. It is a series of guide posts to keep one going in the right direction. 2. It reduces wastage of time and cost. 3. It encourages co-ordination and effective organization. 4. It is a tentative plan which undergoes modifications, as circumstances demand, when the study progresses, new aspects, new conditions and new relationships come to light and insight into the study deepens. 5. It has to be geared to the availability of data and the cooperation of the informants. 6. It has also to be kept within the manageable limits
Question 3: How case study method is useful to Business Research? Answer: Case study is a method of exploring and analyzing the life of a social unit or entity, be it a person, a family, an institution or a community. The aim of case study method is to locate or identify the factors that account for the behaviour patterns of a given unit, and its relationship with the environment. The case data are always gathered with a view to attracting the natural history of the social unit, and its relationship with the social factors and forces operative and involved in this surrounding milieu. In short, the social researcher tries, by means of the case study method, to understand the complex of factors that are working within a social unit as an integrated totality. Looked at from another angle, the case study serves the purpose similar to the clueproviding function of expert opinion. It is most appropriate when one is trying to find clues and ideas for further research. The major credit for introducing case study method into social investigation goes to Frederick Leplay. Herbert Spencer was the first social philosopher who used case study in comparative studies of different cultures. William Healey used case study in his study of juvenile delinquency. Anthropologists and ethnologists have liberally utilized cast study in the systematic description of primitive cultures. Historians have used this method for portraying some historical character or particular historical period and describing the developments within a national community. Advantages of Case Study Method Case study of particular value when a complex set of variables may be at work in generating observed results and intensive study is needed to unravel the complexities. For example, an in-depth study of a firm?s top sales people and comparison with worst salespeople might reveal characteristics common to stellar performers. Here again, the exploratory investigation is best served by an active curiosity and willingness to deviate from the initial plan when findings suggest new courses of inquiry might prove more productive. It is easy to see how the exploratory research objectives of generating insights and hypothesis would be well served by use of this technique. In-depth analysis of selected cases is of particular value to business research when a complex set of variables may be at work in generating observed results and intensive study is needed to unravel the complexities. For instance, an in-depth study of a firm?s top sales people and comparison with the worst sales people might reveal characteristics common to stellar performers. The exploratory investigator is best served by the active curiosity and willingness to deviate from the initial plan, when the finding suggests new courses of enquiry, might prove more productive.
Question 4: Distinguish between schedules and questionnaires. Answer: Meaning of Schedule and Questionnaire The mail survey is another method of collecting primary data. This method involves sending questionnaires to the respondents with a request to complete them and return them by post. This can be used in the case of educated respondents only. The mail questionnaires should be simple so that the respondents can easily understand the questions and answer them. It should preferably contain mostly closed-end and multiple choice questions so that it could be completed within a few minutes. The distinctive feature of the mail survey is that the questionnaire is selfadministered by the respondents themselves and the responses are recorded by them, and not by the investigator as in the case of personal interview method. It does not involve face-to-face conversation between the investigator and the respondent. Communication is carried out only in writing and this required more cooperation from the respondents than in verbal communication.
Distinction between Schedules and Questionnaires Questionnaires are mailed to the respondent whereas schedules are carried by the investigator himself. Questionnaires can be filled by the respondent only if he is able to understand the language in which it is written and he is supposed to be a literate. This problem can be overcome in case of schedule since the investigator himself carries the schedules and the respondent?s response is accordingly taken. A questionnaire is filled by the respondent himself whereas the schedule is filled by the investigator.
Question 5: What are the contents of research reports? Answer: Contents of the Research Report The outline of a research report is given below: I. Prefatory Items · Title page · Declaration · Certificates · Preface/acknowledgements · Table of contents · List of tables · List of graphs/figures/charts · Abstract or synopsis II. Body of the Report · Introduction · Theoretical background of the topic · Statement of the problem · Review of literature · The scope of the study · The objectives of the study · Hypothesis to be tested · Definition of the concepts · Models if any · Design of the study · Methodology · Method of data collection
· Sources of data · Sampling plan · Data collection instruments · Field work · Data processing and analysis plan · Overview of the report · Limitation of the study · Results: findings and discussions · Summary, conclusions and recommendations III. Reference Material · Bibliography · Appendix · Copies of data collection instruments · Technical details on sampling plan · Complex tables · Glossary of new terms used.
Question 6: Write short notes on the following: a) Median b) Standard Deviation Answer: a) Median Median of a set of values is the middle most value when they are arranged in the ascending order of magnitude. (Such an arrangement is called an array). It is a value that is greater than half of the values and lesser than the remaining half. The median is denoted by M. In the case of a raw data and also a discrete frequency distribution, the median is –
value in the arrayed series. In the case of a continuous frequency distribution, the median is –
Where l: lower limit of the median class c: width of the median class. f: frequency of the median class m: less than cumulative frequency unto l. (Cumulative frequency corresponding to the class preceding the median class) N: the total frequency Median class is the class which contains the median. b) Standard Deviation Measures of dispersion range and Q.D are not based on all values. Mean deviation based on all values does not take into consideration the positive or negative sign. Therefore, a measure that removes both drawbacks is given by standard deviation (S.D).
The standard deviation of a set of values is the positive square root of mean of the squared deviations of the values from their arithmetic mean. It is denoted by „s? (sigma). For discrete series without frequency it is given by:
Variance = s= For discrete series with frequency, it is given by:
Variance = s= Where, „X? is the mid value of class interval for continuous series in case of grouped data, alternative form for (A) & (B) are the followings –
For (A)
Variance = s= For (B)
Variance = s= Where, d = X-A: Here, A is assumed mean And C.F.= Class Width
Master of Business Administration-MBA Semester 3 Research Methodology– MB0050 (Book ID: B1206) Assignment Set- 2
Question 1: What is the significance of research in social and business sciences? Answer: Significance of Research in Social and Business Sciences 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 amounts of which makes progress possible. Research encourages scientific and inductive thinking, besides promoting the development of logical habits of thinking and organization. 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 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 the 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 itself it is not a part of research. In the process, research also helps in the proper allocation of a country?s scare 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. Thus, research as a tool of government economic policy formulation involves three distinct stages of operation which are as follows: · Investigation of economic structure through continual compilation of facts
· Diagnoses of events that are taking place and the analysis of the forces underlying them; and · The prognosis, i.e., the prediction of future developments Research also assumes a significant role 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 is 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 analyzing the motivations underlying consumer behaviour. All these researches are very useful for business and industry, which are responsible for business decision making. Research is equally important to social scientist for analyzing social relationships and seeking explanations to various social problems. It gives intellectual satisfaction of knowing things for the sake of knowledge. It also possesses practical utility for the social scientist to gain knowledge so as to be able to do something better or in a more efficient manner. This, research in social sciences is concerned with both knowledge for its own sake, and knowledge for what it can contribute to solve practical problems.
Question 2: What is the meaning of hypothesis? Discuss the type of hypothesis. Answer: Meaning of Hypothesis According to Theodorson and Theodorson, “a hypothesis is a tentative statement asserting a relationship between certain facts. Kerlinger describes it as “a conjectural statement of the relationship between two or more variables”. Black and Champion have described it as “a tentative statement about something, the validity of which is usually unknown”. This statement is intended to be tested empirically and is either verified or rejected. It the statement is not sufficiently established, it is not considered a scientific law. In other words, a hypothesis carries clear implications for testing the stated relationship, i.e., it contains variables that are measurable and specifying how they are related. A statement that lacks variables or that does not explain how the variables are related to each other is no hypothesis in scientific sense. Types of Hypothesis There are many kinds of hypothesis the researcher has to be working with. One type of hypothesis asserts that something is the case in a given instance; that a particular object, person or situation has particular characteristics. Another type of hypothesis deals with the frequency of occurrence or of association among variables; this type of hypothesis may state that X is associated with Y. A certain Y proportion of items e.g. urbanism tends to be accompanied by mental disease or than something are greater or lesser than some other thing in specific settings. Yet another type of hypothesis asserts that a particular characteristics is one of the factors which determine another characteristic, i.e. X is the producer of Y. hypothesis of this type are called causal hypothesis. Null Hypothesis and Alternative Hypothesis In the context of statistical analysis, we often talk null and alternative hypothesis. If we are to compare method A with method B about its superiority and if we proceed on the assumption that both methods are equally good, then this assumption is termed as null hypothesis. As against this, we may think that the method A is superior, it is alternative hypothesis. Symbolically presented as: Null hypothesis = H0 and Alternative hypothesis = Ha Suppose we want to test the hypothesis that the population mean is equal to the hypothesis mean (µ H0) = 100. Then we would say that the null hypotheses are that the population mean is equal to the hypothesized mean 100 and symbolical we can express as: H0: µ= µ H0=100
If our sample results do not support these null hypotheses, we should conclude that something else is true. What we conclude rejecting the null hypothesis is known as alternative hypothesis. If we accept H0, then we are rejecting Ha and if we reject H0, then we are accepting Ha. For H0: µ= µ H0=100, we may consider three possible alternative hypotheses as follows:
The null hypothesis and the alternative hypothesis are chosen before the sample is drawn (the researcher must avoid the error of deriving hypothesis from the data he collects and testing the hypothesis from the same data). In the choice of null hypothesis, the following considerations are usually kept in view: · Alternative hypothesis is usually the one which wishes to prove and the null hypothesis are ones that wish to disprove. Thus a null hypothesis represents the hypothesis we are trying to reject, the alternative hypothesis represents all other possibilities. · If the rejection of a certain hypothesis when it is actually true involves great risk, it is taken as null hypothesis because then the probability of rejecting it when it is true is ? (the level of significance) which is chosen very small. · Null hypothesis should always be specific hypothesis i.e., it should not state about or approximately a certain value. · Generally, in hypothesis testing we proceed on the basis of null hypothesis, keeping the alternative hypothesis in view. Why so? The answer is that on assumption that null hypothesis is true, one can assign the probabilities to different possible sample results, but this cannot be done if we proceed with alternative hypothesis. Hence the use of null hypothesis (at times also known as statistical hypothesis) is quite frequent.
Question 3: Explain the sampling process. Answer: Sampling Process Sampling process consists of seven steps. They are: Step 1: Define the population Population is defined in terms of: · Elements · Sampling units · Extent · Time. Example: If we are monitoring the sale of a new product recently introduced by a company, say (shampoo sachet) the population will be: · Element – Company?s product · Sampling unit – Retail outlet, super market · Extent – Hyderabad and Secunderabad · Time – April 10 to May 10, 2006.
Step 2: Identify the sampling frame Sampling frame could be (a) Telephone Directory (b) Localities of a city using the municipal corporation listing (c) Any other list consisting of all sampling units. Step 3: Specify the sampling unit Individuals who are to be contacted are the sampling units. If retailers are to be contacted in a locality, they are the sampling units. Step 4: Selection of sampling method This refers to whether (a) probability or (b) non-probability methods are used. Step 5: Determine the sample size This means we need to decide “how many elements of the target population are to be chosen?” The sample size depends upon the type of study that is being conducted. For example, If it is an exploratory research, the sample size will be generally small. The sample size also depends upon the resources available with the company. It depends on the accuracy required in the study and the permissible errors allowed. Step 6: Specify the sampling plan A sampling plan should clearly specify the target population. Improper defining would lead to wrong data collection. Example: This means that, if a survey of a household is to be conducted, a sampling plan should define a “household” i.e., “Does the household consist of husband or wife or both”, minors etc., “Who should be included or excluded”. Step 7: Select the sample This is the final step in the sampling process. Based on the above parameters sample respondents may be selected to collect the data for the purpose of research.
Question 4: Distinguish between schedules and questionnaires. Answer: Meaning of Schedule and Questionnaire The mail survey is another method of collecting primary data. This method involves sending questionnaires to the respondents with a request to complete them and return them by post. This can be used in the case of educated respondents only. The mail questionnaires should be simple so that the respondents can easily understand the questions and answer them. It should preferably contain mostly closed-end and multiple choice questions so that it could be completed within a few minutes. The distinctive feature of the mail survey is that the questionnaire is selfadministered by the respondents themselves and the responses are recorded by them, and not by the investigator as in the case of personal interview method. It does not involve face-to-face conversation between the investigator and the respondent. Communication is carried out only in writing and this required more cooperation from the respondents than in verbal communication.
Distinction between Schedules and Questionnaires Questionnaires are mailed to the respondent whereas schedules are carried by the investigator himself. Questionnaires can be filled by the respondent only if he is able to understand the language in which it is written and he is supposed to be a literate. This problem can be overcome in case of schedule since the investigator himself carries the schedules and the respondent?s response is accordingly taken. A questionnaire is filled by the respondent himself whereas the schedule is filled by the investigator.
Question 5: What are the problems encountered in the interview? Answer: Interview Problems In personal interviewing, the researcher must deal with two major problems, inadequate response, non-response and interviewer?s bias. Inadequate response Kahn and Cannel distinguish five principal symptoms of inadequate response. They are: · Partial response, in which the respondent gives a relevant but incomplete answer · Non-response, when the respondent remains silent or refuses to answer the question · Irrelevant response, in which the respondent?s answer is not relevant to the question asked · Inaccurate response, when the reply is biased or distorted and · verbalized response problem, which arises on account of respondent?s failure to understand a question or lack of information necessary for answering it. Interviewer’s Bias The interviewer is an important cause of response bias. He may resort to cheating by „cooking up? data without actually interviewing. The interviewers can influence the responses by inappropriate suggestions, word emphasis, tone of voice and question rephrasing. His own attitudes and expectations about what a particular category of respondents may say or think may bias the data. Another source of response of the interviewer?s characteristics (education, apparent social status, etc) may also bias his answers. Another source of response bias arises from interviewer?s perception of the situation, if he regards the assignment as impossible or sees the results of the survey as possible threats to personal interests or beliefs he is likely to introduce bias. As interviewers are human beings, such biasing factors can never be overcome completely, but their effects can be reduced by careful selection and training of interviewers, proper motivation and supervision, standardization or interview procedures (use of standard wording in survey questions, standard instructions on probing procedure and so on) and standardization of interviewer behaviour. There is need for more research on ways to minimize bias in the interview.
Non-response Non-response refers to failure to obtain responses from some sample respondents. There are many sources of non-response; non-availability, refusal, incapacity and inaccessibility. Non-availability Some respondents may not be available at home at the time of call. This depends upon the nature of the respondent and the time of calls. For example, employed persons may not be available during working hours. Farmers may not be available at home during cultivation season. Selection of appropriate timing for calls could solve this problem. Evenings and weekends may be favourable interviewing hours for such respondents. If someone is available, then, line respondent?s hours of availability can be ascertained and the next visit can be planned accordingly. Refusal Some persons may refuse to furnish information because they are ill-disposed, or approached at the wrong hour and so on. Although, a hardcore of refusals remains, another try or perhaps another approach may find some of them cooperative. Incapacity or inability may refer to illness which prevents a response during the entire survey period. This may also arise on account of language barrier. Inaccessibility Some respondents may be inaccessible. Some may not be found due to migration and other reasons. Non-responses reduce the effective sample size and its representativeness.
Question 6: Write short notes on following a) Dispersion b) Mathematical averages Answer: Dispersion Dispersion is the tendency of the individual values in a distribution to spread away from the average. Many economic variables like income, wage etc., are widely varied from the mean. Dispersion is a statistical measure, which understands the degree of variation of items from the average. Objectives of Measuring Dispersion Study of dispersion is needed to: 1. To test the reliability of the average 2. To control variability of the data 3. To enable comparison with two or more distribution with regard to their variability 4. To facilitate the use of other statistical measures. Measures of dispersion points out as to how far the average value is representative of the individual items. If the dispersion value is small, the average tends to closely represent the individual values and it is reliable. When dispersion is large, the average is not a typical representative value. Measures of dispersion are useful to control the cause of variation. In industrial production, efficient operation requires control of quality variation. Measures of variation enable comparison of two or more series with regard to their variability. A high degree of variation would mean little consistency and low degree of variation would mean high consistency. Properties of a Good Measure of Dispersion A good measure of dispersion should be simple to understand. 1. 2. 3. 4. It should be easy to calculate It should be rigidly defined It should be based on all the values of a distribution It should be amenable to further statistical and algebraic treatment.
5. 6.
It should have sampling stability It should not be unduly affected by extreme values.
Measures of Dispersion 1. 2. 3. 4. 5. Range Quartile deviation Mean deviation Standard deviation Lorenz curve
Range, Quartile deviation, Mean deviation and Standard deviation are mathematical measures of dispersion. Lorenz curve is a graphical measure of dispersion. Measures of dispersion can be absolute or relative. An absolute measure of dispersion is expressed in the same unit of the original data. When two sets of data are expressed in different units, relative measures of dispersion are used for comparison. A relative measure of dispersion is the ratio of absolute measure to an appropriate average. The following are the important relative measures of dispersion. 1. 2. 3. 4. Coefficient of range Coefficient of Quartile deviation Coefficient of Mean deviation Coefficient of Standard deviation.
Mathematical Averages Arithmetic mean, geometric mean and harmonic mean are mathematical averages. Median and mode are positional averages. These statistical measures try to understand how individual values in a distribution concentrate to a central value like average. If the values of distribution approximately come near to the average value, we conclude that the distribution has central tendency. Arithmetic Mean Arithmetic mean is the most commonly used statistical average. It is the value obtained by dividing the sum of the item by the number of items in a series. Symbolically we say
When frequencies are also given with the values, to calculate arithmetic mean, the values are first multiplied with the corresponding frequency. Then their sum is divided by the number of frequency. Thus in a discrete series, arithmetic mean is calculated by the following formula. Arithmetic mean Where, = =
= sum the values multiplied by the corresponding frequency. sum of the frequency
If x1 x2 x3… xn are the values of a series, and f1 f2 f3… fn are their corresponding frequencies, Arithmetic mean is calculated by (f1 x1 + f2 x2 + f3x3… + fn xn) / (f1 + f2 + f3… + fn) or Arithmetic mean = Geometric Mean Geometric mean is defined as the nth root of the product of N items of a series. If there are two items in the data, we take the square root; if there are three items we take the cube root, and so on. Symbolically, GM =
Where x1, x2. ..xn are the items of the given series. To simplify calculations, logarithms are used. Accordingly, GM =
In discrete series GM =
Harmonic Mean In individual series HM In discrete series HM N M = = = N / Sf (1/m) Total frequency Mi values of the class = N / S(1/x)
doc_205234759.docx
Methodology is the systematic, theoretical analysis of the methods applied to a field of study, or the theoretical analysis of the body of methods and principles associated with a branch of knowledge.
Master of Business Administration-MBA Semester 3 Research Methodology– MB0050 (Book ID: B1206) Assignment Set- 1
Question 1: How is a research problem formulated? Answer: Formulating the Problem The selection of one appropriate researchable problem out of the identified problems requires evaluation of those alternatives against certain criteria, which may be grouped into: Internal Criteria Internal Criteria consists of: 1) Researcher?s interest: The problem should interest the researcher and be a challenge to him. Without interest and curiosity, he may not develop sustained perseverance. Even a small difficulty may become an excuse for discontinuing the study. Interest in a problem depends upon the researcher?s educational background, experience, outlook and sensitivity. 2) Researcher?s competence: A mere interest in a problem will not do. The researcher must be competent to plan and carry out a study of the problem. He must have the ability to grasp and deal with int. he must possess adequate knowledge of the subject-matter, relevant methodology and statistical procedures. 3) Researcher?s own resource: In the case of a research to be done by a researcher on his own, consideration of his own financial resource is pertinent. If it is beyond his means, he will not be able to complete the work, unless he gets some external financial support. Time resource is more important than finance. Research is a timeconsuming process; hence it should be properly utilized. External Criteria 1) Research-ability of the problem: The problem should be researchable, i.e., amendable for finding answers to the questions involved in it through scientific
method. To be researchable a question must be one for which observation or other data collection in the real world can provide the answer. 2) Importance and urgency: Problems requiring investigation are unlimited, but available research efforts are very much limited. Therefore, in selecting problems for research, their relative importance and significance should be considered. An important and urgent problem should be given priority over an unimportant one. 3) Novelty of the problem: The problem must have novelty. There is no use of wasting one?s time and energy on a problem already studied thoroughly by others. This does not mean that replication is always needless. In social sciences in some cases, it is appropriate to replicate (repeat) a study in order to verify the validity of its findings to a different situation. 4) Feasibility: A problem may be a new one and also important, but if research on it is not feasible, it cannot be selected. Hence feasibility is a very important consideration. 5) Facilities: Research requires certain facilities such as well-equipped library facility, suitable and competent guidance, data analysis facility, etc. Hence the availability of the facilities relevant to the problem must be considered. 6) Usefulness and social relevance: Above all, the study of the problem should make significant contribution to the concerned body of knowledge or to the solution of some significant practical problem. It should be socially relevant. This consideration is particularly important in the case of higher level academic research and sponsored research. 7) Research personnel: Research undertaken by professors and by research organizations require the services of investigators and research officers. But in India and other developing countries, research has not yet become a prospective profession. Hence talent persons are not attracted to research projects. Each identified problem must be evaluated in terms of the above internal and external criteria and the most appropriate one may be selected by a research scholar.
Question 2: What are the characteristics of a good research design? Answer: Characteristics of a Good Research Design
1. It is a series of guide posts to keep one going in the right direction. 2. It reduces wastage of time and cost. 3. It encourages co-ordination and effective organization. 4. It is a tentative plan which undergoes modifications, as circumstances demand, when the study progresses, new aspects, new conditions and new relationships come to light and insight into the study deepens. 5. It has to be geared to the availability of data and the cooperation of the informants. 6. It has also to be kept within the manageable limits
Question 3: How case study method is useful to Business Research? Answer: Case study is a method of exploring and analyzing the life of a social unit or entity, be it a person, a family, an institution or a community. The aim of case study method is to locate or identify the factors that account for the behaviour patterns of a given unit, and its relationship with the environment. The case data are always gathered with a view to attracting the natural history of the social unit, and its relationship with the social factors and forces operative and involved in this surrounding milieu. In short, the social researcher tries, by means of the case study method, to understand the complex of factors that are working within a social unit as an integrated totality. Looked at from another angle, the case study serves the purpose similar to the clueproviding function of expert opinion. It is most appropriate when one is trying to find clues and ideas for further research. The major credit for introducing case study method into social investigation goes to Frederick Leplay. Herbert Spencer was the first social philosopher who used case study in comparative studies of different cultures. William Healey used case study in his study of juvenile delinquency. Anthropologists and ethnologists have liberally utilized cast study in the systematic description of primitive cultures. Historians have used this method for portraying some historical character or particular historical period and describing the developments within a national community. Advantages of Case Study Method Case study of particular value when a complex set of variables may be at work in generating observed results and intensive study is needed to unravel the complexities. For example, an in-depth study of a firm?s top sales people and comparison with worst salespeople might reveal characteristics common to stellar performers. Here again, the exploratory investigation is best served by an active curiosity and willingness to deviate from the initial plan when findings suggest new courses of inquiry might prove more productive. It is easy to see how the exploratory research objectives of generating insights and hypothesis would be well served by use of this technique. In-depth analysis of selected cases is of particular value to business research when a complex set of variables may be at work in generating observed results and intensive study is needed to unravel the complexities. For instance, an in-depth study of a firm?s top sales people and comparison with the worst sales people might reveal characteristics common to stellar performers. The exploratory investigator is best served by the active curiosity and willingness to deviate from the initial plan, when the finding suggests new courses of enquiry, might prove more productive.
Question 4: Distinguish between schedules and questionnaires. Answer: Meaning of Schedule and Questionnaire The mail survey is another method of collecting primary data. This method involves sending questionnaires to the respondents with a request to complete them and return them by post. This can be used in the case of educated respondents only. The mail questionnaires should be simple so that the respondents can easily understand the questions and answer them. It should preferably contain mostly closed-end and multiple choice questions so that it could be completed within a few minutes. The distinctive feature of the mail survey is that the questionnaire is selfadministered by the respondents themselves and the responses are recorded by them, and not by the investigator as in the case of personal interview method. It does not involve face-to-face conversation between the investigator and the respondent. Communication is carried out only in writing and this required more cooperation from the respondents than in verbal communication.
Distinction between Schedules and Questionnaires Questionnaires are mailed to the respondent whereas schedules are carried by the investigator himself. Questionnaires can be filled by the respondent only if he is able to understand the language in which it is written and he is supposed to be a literate. This problem can be overcome in case of schedule since the investigator himself carries the schedules and the respondent?s response is accordingly taken. A questionnaire is filled by the respondent himself whereas the schedule is filled by the investigator.
Question 5: What are the contents of research reports? Answer: Contents of the Research Report The outline of a research report is given below: I. Prefatory Items · Title page · Declaration · Certificates · Preface/acknowledgements · Table of contents · List of tables · List of graphs/figures/charts · Abstract or synopsis II. Body of the Report · Introduction · Theoretical background of the topic · Statement of the problem · Review of literature · The scope of the study · The objectives of the study · Hypothesis to be tested · Definition of the concepts · Models if any · Design of the study · Methodology · Method of data collection
· Sources of data · Sampling plan · Data collection instruments · Field work · Data processing and analysis plan · Overview of the report · Limitation of the study · Results: findings and discussions · Summary, conclusions and recommendations III. Reference Material · Bibliography · Appendix · Copies of data collection instruments · Technical details on sampling plan · Complex tables · Glossary of new terms used.
Question 6: Write short notes on the following: a) Median b) Standard Deviation Answer: a) Median Median of a set of values is the middle most value when they are arranged in the ascending order of magnitude. (Such an arrangement is called an array). It is a value that is greater than half of the values and lesser than the remaining half. The median is denoted by M. In the case of a raw data and also a discrete frequency distribution, the median is –
value in the arrayed series. In the case of a continuous frequency distribution, the median is –
Where l: lower limit of the median class c: width of the median class. f: frequency of the median class m: less than cumulative frequency unto l. (Cumulative frequency corresponding to the class preceding the median class) N: the total frequency Median class is the class which contains the median. b) Standard Deviation Measures of dispersion range and Q.D are not based on all values. Mean deviation based on all values does not take into consideration the positive or negative sign. Therefore, a measure that removes both drawbacks is given by standard deviation (S.D).
The standard deviation of a set of values is the positive square root of mean of the squared deviations of the values from their arithmetic mean. It is denoted by „s? (sigma). For discrete series without frequency it is given by:
Variance = s= For discrete series with frequency, it is given by:
Variance = s= Where, „X? is the mid value of class interval for continuous series in case of grouped data, alternative form for (A) & (B) are the followings –
For (A)
Variance = s= For (B)
Variance = s= Where, d = X-A: Here, A is assumed mean And C.F.= Class Width
Master of Business Administration-MBA Semester 3 Research Methodology– MB0050 (Book ID: B1206) Assignment Set- 2
Question 1: What is the significance of research in social and business sciences? Answer: Significance of Research in Social and Business Sciences 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 amounts of which makes progress possible. Research encourages scientific and inductive thinking, besides promoting the development of logical habits of thinking and organization. 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 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 the 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 itself it is not a part of research. In the process, research also helps in the proper allocation of a country?s scare 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. Thus, research as a tool of government economic policy formulation involves three distinct stages of operation which are as follows: · Investigation of economic structure through continual compilation of facts
· Diagnoses of events that are taking place and the analysis of the forces underlying them; and · The prognosis, i.e., the prediction of future developments Research also assumes a significant role 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 is 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 analyzing the motivations underlying consumer behaviour. All these researches are very useful for business and industry, which are responsible for business decision making. Research is equally important to social scientist for analyzing social relationships and seeking explanations to various social problems. It gives intellectual satisfaction of knowing things for the sake of knowledge. It also possesses practical utility for the social scientist to gain knowledge so as to be able to do something better or in a more efficient manner. This, research in social sciences is concerned with both knowledge for its own sake, and knowledge for what it can contribute to solve practical problems.
Question 2: What is the meaning of hypothesis? Discuss the type of hypothesis. Answer: Meaning of Hypothesis According to Theodorson and Theodorson, “a hypothesis is a tentative statement asserting a relationship between certain facts. Kerlinger describes it as “a conjectural statement of the relationship between two or more variables”. Black and Champion have described it as “a tentative statement about something, the validity of which is usually unknown”. This statement is intended to be tested empirically and is either verified or rejected. It the statement is not sufficiently established, it is not considered a scientific law. In other words, a hypothesis carries clear implications for testing the stated relationship, i.e., it contains variables that are measurable and specifying how they are related. A statement that lacks variables or that does not explain how the variables are related to each other is no hypothesis in scientific sense. Types of Hypothesis There are many kinds of hypothesis the researcher has to be working with. One type of hypothesis asserts that something is the case in a given instance; that a particular object, person or situation has particular characteristics. Another type of hypothesis deals with the frequency of occurrence or of association among variables; this type of hypothesis may state that X is associated with Y. A certain Y proportion of items e.g. urbanism tends to be accompanied by mental disease or than something are greater or lesser than some other thing in specific settings. Yet another type of hypothesis asserts that a particular characteristics is one of the factors which determine another characteristic, i.e. X is the producer of Y. hypothesis of this type are called causal hypothesis. Null Hypothesis and Alternative Hypothesis In the context of statistical analysis, we often talk null and alternative hypothesis. If we are to compare method A with method B about its superiority and if we proceed on the assumption that both methods are equally good, then this assumption is termed as null hypothesis. As against this, we may think that the method A is superior, it is alternative hypothesis. Symbolically presented as: Null hypothesis = H0 and Alternative hypothesis = Ha Suppose we want to test the hypothesis that the population mean is equal to the hypothesis mean (µ H0) = 100. Then we would say that the null hypotheses are that the population mean is equal to the hypothesized mean 100 and symbolical we can express as: H0: µ= µ H0=100
If our sample results do not support these null hypotheses, we should conclude that something else is true. What we conclude rejecting the null hypothesis is known as alternative hypothesis. If we accept H0, then we are rejecting Ha and if we reject H0, then we are accepting Ha. For H0: µ= µ H0=100, we may consider three possible alternative hypotheses as follows:
The null hypothesis and the alternative hypothesis are chosen before the sample is drawn (the researcher must avoid the error of deriving hypothesis from the data he collects and testing the hypothesis from the same data). In the choice of null hypothesis, the following considerations are usually kept in view: · Alternative hypothesis is usually the one which wishes to prove and the null hypothesis are ones that wish to disprove. Thus a null hypothesis represents the hypothesis we are trying to reject, the alternative hypothesis represents all other possibilities. · If the rejection of a certain hypothesis when it is actually true involves great risk, it is taken as null hypothesis because then the probability of rejecting it when it is true is ? (the level of significance) which is chosen very small. · Null hypothesis should always be specific hypothesis i.e., it should not state about or approximately a certain value. · Generally, in hypothesis testing we proceed on the basis of null hypothesis, keeping the alternative hypothesis in view. Why so? The answer is that on assumption that null hypothesis is true, one can assign the probabilities to different possible sample results, but this cannot be done if we proceed with alternative hypothesis. Hence the use of null hypothesis (at times also known as statistical hypothesis) is quite frequent.
Question 3: Explain the sampling process. Answer: Sampling Process Sampling process consists of seven steps. They are: Step 1: Define the population Population is defined in terms of: · Elements · Sampling units · Extent · Time. Example: If we are monitoring the sale of a new product recently introduced by a company, say (shampoo sachet) the population will be: · Element – Company?s product · Sampling unit – Retail outlet, super market · Extent – Hyderabad and Secunderabad · Time – April 10 to May 10, 2006.
Step 2: Identify the sampling frame Sampling frame could be (a) Telephone Directory (b) Localities of a city using the municipal corporation listing (c) Any other list consisting of all sampling units. Step 3: Specify the sampling unit Individuals who are to be contacted are the sampling units. If retailers are to be contacted in a locality, they are the sampling units. Step 4: Selection of sampling method This refers to whether (a) probability or (b) non-probability methods are used. Step 5: Determine the sample size This means we need to decide “how many elements of the target population are to be chosen?” The sample size depends upon the type of study that is being conducted. For example, If it is an exploratory research, the sample size will be generally small. The sample size also depends upon the resources available with the company. It depends on the accuracy required in the study and the permissible errors allowed. Step 6: Specify the sampling plan A sampling plan should clearly specify the target population. Improper defining would lead to wrong data collection. Example: This means that, if a survey of a household is to be conducted, a sampling plan should define a “household” i.e., “Does the household consist of husband or wife or both”, minors etc., “Who should be included or excluded”. Step 7: Select the sample This is the final step in the sampling process. Based on the above parameters sample respondents may be selected to collect the data for the purpose of research.
Question 4: Distinguish between schedules and questionnaires. Answer: Meaning of Schedule and Questionnaire The mail survey is another method of collecting primary data. This method involves sending questionnaires to the respondents with a request to complete them and return them by post. This can be used in the case of educated respondents only. The mail questionnaires should be simple so that the respondents can easily understand the questions and answer them. It should preferably contain mostly closed-end and multiple choice questions so that it could be completed within a few minutes. The distinctive feature of the mail survey is that the questionnaire is selfadministered by the respondents themselves and the responses are recorded by them, and not by the investigator as in the case of personal interview method. It does not involve face-to-face conversation between the investigator and the respondent. Communication is carried out only in writing and this required more cooperation from the respondents than in verbal communication.
Distinction between Schedules and Questionnaires Questionnaires are mailed to the respondent whereas schedules are carried by the investigator himself. Questionnaires can be filled by the respondent only if he is able to understand the language in which it is written and he is supposed to be a literate. This problem can be overcome in case of schedule since the investigator himself carries the schedules and the respondent?s response is accordingly taken. A questionnaire is filled by the respondent himself whereas the schedule is filled by the investigator.
Question 5: What are the problems encountered in the interview? Answer: Interview Problems In personal interviewing, the researcher must deal with two major problems, inadequate response, non-response and interviewer?s bias. Inadequate response Kahn and Cannel distinguish five principal symptoms of inadequate response. They are: · Partial response, in which the respondent gives a relevant but incomplete answer · Non-response, when the respondent remains silent or refuses to answer the question · Irrelevant response, in which the respondent?s answer is not relevant to the question asked · Inaccurate response, when the reply is biased or distorted and · verbalized response problem, which arises on account of respondent?s failure to understand a question or lack of information necessary for answering it. Interviewer’s Bias The interviewer is an important cause of response bias. He may resort to cheating by „cooking up? data without actually interviewing. The interviewers can influence the responses by inappropriate suggestions, word emphasis, tone of voice and question rephrasing. His own attitudes and expectations about what a particular category of respondents may say or think may bias the data. Another source of response of the interviewer?s characteristics (education, apparent social status, etc) may also bias his answers. Another source of response bias arises from interviewer?s perception of the situation, if he regards the assignment as impossible or sees the results of the survey as possible threats to personal interests or beliefs he is likely to introduce bias. As interviewers are human beings, such biasing factors can never be overcome completely, but their effects can be reduced by careful selection and training of interviewers, proper motivation and supervision, standardization or interview procedures (use of standard wording in survey questions, standard instructions on probing procedure and so on) and standardization of interviewer behaviour. There is need for more research on ways to minimize bias in the interview.
Non-response Non-response refers to failure to obtain responses from some sample respondents. There are many sources of non-response; non-availability, refusal, incapacity and inaccessibility. Non-availability Some respondents may not be available at home at the time of call. This depends upon the nature of the respondent and the time of calls. For example, employed persons may not be available during working hours. Farmers may not be available at home during cultivation season. Selection of appropriate timing for calls could solve this problem. Evenings and weekends may be favourable interviewing hours for such respondents. If someone is available, then, line respondent?s hours of availability can be ascertained and the next visit can be planned accordingly. Refusal Some persons may refuse to furnish information because they are ill-disposed, or approached at the wrong hour and so on. Although, a hardcore of refusals remains, another try or perhaps another approach may find some of them cooperative. Incapacity or inability may refer to illness which prevents a response during the entire survey period. This may also arise on account of language barrier. Inaccessibility Some respondents may be inaccessible. Some may not be found due to migration and other reasons. Non-responses reduce the effective sample size and its representativeness.
Question 6: Write short notes on following a) Dispersion b) Mathematical averages Answer: Dispersion Dispersion is the tendency of the individual values in a distribution to spread away from the average. Many economic variables like income, wage etc., are widely varied from the mean. Dispersion is a statistical measure, which understands the degree of variation of items from the average. Objectives of Measuring Dispersion Study of dispersion is needed to: 1. To test the reliability of the average 2. To control variability of the data 3. To enable comparison with two or more distribution with regard to their variability 4. To facilitate the use of other statistical measures. Measures of dispersion points out as to how far the average value is representative of the individual items. If the dispersion value is small, the average tends to closely represent the individual values and it is reliable. When dispersion is large, the average is not a typical representative value. Measures of dispersion are useful to control the cause of variation. In industrial production, efficient operation requires control of quality variation. Measures of variation enable comparison of two or more series with regard to their variability. A high degree of variation would mean little consistency and low degree of variation would mean high consistency. Properties of a Good Measure of Dispersion A good measure of dispersion should be simple to understand. 1. 2. 3. 4. It should be easy to calculate It should be rigidly defined It should be based on all the values of a distribution It should be amenable to further statistical and algebraic treatment.
5. 6.
It should have sampling stability It should not be unduly affected by extreme values.
Measures of Dispersion 1. 2. 3. 4. 5. Range Quartile deviation Mean deviation Standard deviation Lorenz curve
Range, Quartile deviation, Mean deviation and Standard deviation are mathematical measures of dispersion. Lorenz curve is a graphical measure of dispersion. Measures of dispersion can be absolute or relative. An absolute measure of dispersion is expressed in the same unit of the original data. When two sets of data are expressed in different units, relative measures of dispersion are used for comparison. A relative measure of dispersion is the ratio of absolute measure to an appropriate average. The following are the important relative measures of dispersion. 1. 2. 3. 4. Coefficient of range Coefficient of Quartile deviation Coefficient of Mean deviation Coefficient of Standard deviation.
Mathematical Averages Arithmetic mean, geometric mean and harmonic mean are mathematical averages. Median and mode are positional averages. These statistical measures try to understand how individual values in a distribution concentrate to a central value like average. If the values of distribution approximately come near to the average value, we conclude that the distribution has central tendency. Arithmetic Mean Arithmetic mean is the most commonly used statistical average. It is the value obtained by dividing the sum of the item by the number of items in a series. Symbolically we say
When frequencies are also given with the values, to calculate arithmetic mean, the values are first multiplied with the corresponding frequency. Then their sum is divided by the number of frequency. Thus in a discrete series, arithmetic mean is calculated by the following formula. Arithmetic mean Where, = =
= sum the values multiplied by the corresponding frequency. sum of the frequency
If x1 x2 x3… xn are the values of a series, and f1 f2 f3… fn are their corresponding frequencies, Arithmetic mean is calculated by (f1 x1 + f2 x2 + f3x3… + fn xn) / (f1 + f2 + f3… + fn) or Arithmetic mean = Geometric Mean Geometric mean is defined as the nth root of the product of N items of a series. If there are two items in the data, we take the square root; if there are three items we take the cube root, and so on. Symbolically, GM =
Where x1, x2. ..xn are the items of the given series. To simplify calculations, logarithms are used. Accordingly, GM =
In discrete series GM =
Harmonic Mean In individual series HM In discrete series HM N M = = = N / Sf (1/m) Total frequency Mi values of the class = N / S(1/x)
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