Syllabus: B.B.A. V Sem Subject - Research Methodology
Syllabus: B.B.A. V Sem Subject - Research Methodology
Syllabus: B.B.A. V Sem Subject - Research Methodology
SYLLABUS
B.B.A. V SEM
Subject – Research Methodology
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Unit – 1
MEANING & TYPES OF RESEARCH
Meaning:
1) Gathering and analyzing a body of information or data and extracting new meaning from it or
developing unique solutions to problems or cases.
2) A report or review, not designed to create new information or insight but to collate and
synthesize existing information.
3) A search for individual facts or data. May be part of the search for a solution to a larger
problem
Types :
There are two types of research which can be done to develop a thesis or dissertation:
1) Practical Research: The practical approach consists of the empirical study of the topic under
research and chiefly consists of hands on approach. This involves first hand research in the form
of questionnaires, surveys, interviews, observations and discussion groups.
2) Theoretical Research: A non empirical approach to research, this usually involves perusal of
mostly published works like researching through archives of public libraries, court rooms and
published academic journals.
3) Descriptive/Qualitative: This type of research methods involve describing in details specific
situation using research tools like interviews, surveys, and Observations. It focuses on gathering
of mainly verbal data rather than measurements.
4) Descriptive/Quantitative: This type of research methods requires quantifiable data involving
numerical and statistical explanations. Quantitative analysis hinges on researchers
understanding the assumptions inherent within different statistical models. It generates
numerical data or information that can be converted into numbers. The presentation of data is
through tables containing data in the form of numbers and statistics.
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3. Research design: The third step in a research process is to prepare research design.
Research design is a plan for conducting a research. It guides the researcher in data collection. It gives
proper direction to the research.
There are three types of research designs:
1. Exploratory research,
2. Descriptive Research and
3. Experimental Research.
All three types are used for marketing research.
4. Determining data needs: The fourth step in a research process is to determine the data needs. The
researcher must consider the following issues:
1. Whether to use primary data or secondary data or both.
2. The accuracy and reliability of the data.
3. The availability of accurate and reliable data.
4. The cost and time required to collect the data.
5. Determining data sources: The fifth step in a research process is to determine the data sources.
The researcher decides the sources of collecting data. The two main sources are secondary data and
primary data. The researcher first collects secondary data. This is because it is easily available and less
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costly. It is collected by Desk Research. Desk Research can be internal for e.g. collected from company's
records or external i.e. acquired from libraries, trade journals, government sources, etc. If the
secondary data is not sufficient to solve the marketing problem, then primary data is wheeled.
Collecting primary data is very costly and time consuming. It can be collected by using survey methods,
i.e. by doing personal interviews, telephone interviews and mail surveys. It can also be collected by
using observational method and experimentation method.
So in this step the researcher decides what source and what method to use for collecting data.
6. Sampling design: The sixth step in a research process is of sampling design. The Researchers has
limited time and other resources. So he cannot contact the total population. That is, he cannot collect
information from all the people in the market. Therefore, he selects few persons from the population.
These handful persons are called sample respondent. They are considered to represent the total
population. The researcher collects data from the sample respondents. Sampling helps to save time,
efforts and cost. It is used to collect primary data. The researcher has to decide about method of
sampling, the size-of-sample, etc.
8. Field staff selection: The eighth step in a research process is of selecting field staff. After preparing
the questionnaire, the researcher selects field interviewers. The field interviewers collect information
from the respondents. They must be property trained. Students of psychology and statistics are good
for this job.
9. Collection and processing of data: The ninth step in a research process is of collection and
processing of data. In this stage, the data is collected from the respondents. The questionnaire is used
for collecting data. In case of mail surveys, the questionnaire is sent to the respondents by post. In case
of telephone interviews, the data is collected through telephone. In case of personal interviews, the data
is collected by the field interviewers. The researcher can also use observation method and
experimentation method for collecting data. The data collected must be reliable and complete. It must
also be collected quickly. Secondary data is also collected. The data collected is raw. It cannot be used
directly. It has to be processed and organized neatly. That is, the data must be edited, coded, classified
and tabulated. Editing helps to remove the unwanted data. Coding, classification and tabulation make
the data ready for analysis and interpretation.
10. Analysis and interpretation of data: The tenth step in a research process is of analysis and
interpretation of data. In this stage, the researcher analyzes and interprets the data. That is, he studies
the data very careful and draws conclusions from it. These conclusions are then used to solve the
marketing problem.
11. Project reporting: The eleventh step in a research process is to prepare a project report.
In this stage, the researcher prepares the final research report. This report contains a title of the report,
method used, findings, conclusions and suggestions about how to solve the marketing problem. The
language of the report must not be very difficult. The report must be submitted to the marketing
executives for recommendations and implementation.
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12. Follow up: Finally, the last step in a research process is to do a follow up.
In this stage, the marketing executive makes changes in the product, price, marketing policies, etc. as
per the recommendations of the report. Here, the researcher should find out, whether his
recommendations are implemented properly or not. He should also figure-out, whether the marketing
problem is solved or not.
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1) Targeted Issues are addressed. The organization asking for the research has the complete control
on the process and the research is streamlines as far as its objectives and scope is concerned.
Researching company can be asked to concentrate their efforts to find data regarding specific market
rather than concentration on mass market.
2) Data interpretation is better. The collected data can be examined and interpreted by the
marketers depending on their needs rather than relying on the interpretation made by collectors of
secondary data.
3) Fresh/Recent Data. Usually secondary data is not so recent and it may not be specific to the place or
situation marketer is targeting. The researcher can use the irrelevant seeming information for knowing
trends or may be able to find some relation with the current scenario. Thus primary data becomes a
more accurate tool since we can use data which is useful for us.
4) Proprietary Issues. Collector of primary data is the owner of that information and he need not
share it with other companies and competitors. This gives an edge over competitors replying on
secondary data.
Disadvantages of Primary data:
1) High Cost. Collecting data using primary research is a costly proposition as marketer has to be
involved throughout and has to design everything.
2) Time Consuming. Because of exhaustive nature of the exercise, the time required to do research
accurately is very long as compared to secondary data, which can be collected in much lesser time
duration.
3) Inaccurate Feed-backs. In case the research involves taking feedbacks from the targeted audience,
there are high chances that feedback given is not correct. Feedbacks by their basic nature are usually
biased or given just for the sake of it.
4) More number of resources are required. Leaving aside cost and time, other resources like human
resources and materials too are needed in larger quantity to do surveys and data collection.
Secondary Data:
Secondary data, is data collected by someone other than the user. Common sources of secondary data
for social science include censuses, organisational records and data collected through qualitative
methodologies or qualitative research. Primary data, by contrast, are collected by the investigator
conducting the research.
Sources of secondary data:
Secondary sources are data that already exists
1. Previous research
2. Official statistics
3. Mass media products
4. Diaries
5. Letters
6. Government reports
7. Web information
8. Historical data and information
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Unit 2
RESEARCH DESIGN
Variables & Types of Variables
When it comes to experiments and data analysis, there are two main types of variables: dependent
variables and independent variables. It’s easy to get these mixed up, but the difference between
dependent and independent variables is simple. Here is a quick and easy definition of each one, along
with some examples.
1) Dependent Variable: This is the output variable you are really interested in monitoring to see if it
was affected or not. It can also be called the “measured variable,” the “responding variable,” the
“explained variable,” etc. I think it is easy to remember this one because it is dependent on the other
variables.
2) Independent Variables: These are the individual variables that you believe may have an effect on
the dependent variable. They are sometimes called “explanatory variables,” “manipulated variables,” or
“controlled variables.”
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these words indicate towards the support they provide to each other on the placement of the hypothesis
under the evidence, which acts as a foundation.
According to George A Luniberg, hypothesis can be defined as a ‘tentative generalization, the validity of
which remains to be tested. In this elementary stage, the hypothesis may be very hunch, guess,
imaginative data, which becomes the basis for an action or an investigation.’
A very vital point that should be kept in mind about the hypotheses is that these are not theories these
only have some linkage to the theory but hypothesis is not that much elaborated as the theory is. But it
can be said that the hypothesis is derived from the theory.
Sources of hypothesis
1. Observations made in routine activities.
2. Theories based on the scientific approach.
3. Analogies.
4. Knowledge obtained from the functional executives.
5. Results of the research and development department.
6. Experience of the investigator.
Characteristics of hypothesis
1. Should be very specific in nature.
2. Concept of the hypothesis should be clear.
3. Should be empirically testable.
4. Should be related to the devices and the techniques that are available.
5. Should relate to the body of the theory.
6. Should recognize the specific variables and their relation
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3. Representative fictions – Some hypothesis are based on the assumptions and depending on the
nature of the case, it is not at all possible to prove these assumptions by the direct means such
hypothesis is referred to as the representative fictions. The only positive point of these representative
fictions is that they are very suitable in order to explain the whole phenomenon.
Exploratory research on the other hand seeks to generate a posteriori hypotheses by examining a data-
set and looking for potential relations between variables. It is also possible to have an idea about a
relation between variables but to lack knowledge of the direction and strength of the relation. If the
researcher does not have any specific hypotheses beforehand, the study is exploratory with respect to
the variables in question (although it might be confirmatory for others). The advantage of exploratory
research is that it is easier to make new discoveries due to the less stringent methodological restrictions.
Here, the researcher does not want to miss a potentially interesting relation and therefore aims to
minimize the probability of rejecting a real effect or relation, this probability is sometimes referred to as
β and the associated error is of type II. In other words, if you want to see whether some of your
measured variables could be related, you would want to increase your chances of finding a significant
result by lowering the threshold of what you deem to be significant.
Sometimes, a researcher may conduct exploratory research but report it as if it had been confirmatory
this is a questionable research practice bordering fraud.
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UNIT 3
MEASUREMENT METHODS
Interview Research
1) The qualitative research interview seeks to describe and the meanings of central themes in the life
world of the subjects. The main task in interviewing is to understand the meaning of what the
interviewees say.
2) A qualitative research interview seeks to cover both a factual and a meaning level, though it is
usually more difficult to interview on a meaning level.
3) Interviews are particularly useful for getting the story behind a participant’s experiences. The
interviewer can pursue in-depth information around the topic. Interviews may be useful as follow-
up to certain respondents to questionnaires, e.g., to further investigate their responses.
Characteristics of Interview
1) Interviews are completed by the interviewer based on what the respondent says.
2) Interviews are a far more personal form of research than questionnaires.
3) In the personal interview, the interviewer works directly with the respondent
4) Unlike with mail surveys, the interviewer has the opportunity toprobe or ask follow up questions.
5) Interviews are generally easier for respondent, especially if what is sought is opinions or
impressions.
6) Interviews are time consuming and they are resource intensive.
7) The interviewer is considered a part of the measurement instrument and interviewer has to well
trained in how to respond to any contingency
Types of Interviews
1) Informal, conversational interview -no predetermined questions are asked, in order to remain as
open and adaptable as possible to the interviewee’s nature and priorities; during the interview the
interviewer “goes with the flow”.
2) General interview guide approach -the guide approach is intended to ensure that the same
general areas of information are collected from each interviewee; this provides more focus than the
conversational approach, but still allows a degree of freedom and adaptability in getting the
information from the interviewee.
3) Standardized, open-ended interview -the same open-ended questions are asked to all
interviewees; this approach facilitates faster interviews that can be more easily analyzed and
compared.
4) Closed, fixed-response interview -where all interviewees are asked the same questions and asked
to choose answers from among the same set of alternatives. This format is useful for those not
practiced in interviewing
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Questionnaires have been developed over the years. Today, questionnaires are utilized in various
survey methods, according to how they are given. These methods include the self-administered, the
group-administered, and the household drop-off. Among the three, the self-administered survey
method is often used by researchers nowadays. The self-administered questionnaires are widely
known as the mail survey method. However, since the response rates related to mail surveys had gone
low, questionnaires are now commonly administered online, as in the form of web surveys.
Advantages: Ideal for asking closed-ended questions; effective for market or consumer
research
Disadvantages: Limit the researcher’s understanding of the respondent’s answers; requires
budget for reproduction of survey questionnaires
2. Interviews
Between the two broad types of surveys, interviews are more personal and probing. Questionnaires do
not provide the freedom to ask follow-up questions to explore the answers of the respondents, but
interviews do.
An interview includes two persons - the researcher as the interviewer, and the respondent as the
interviewee. There are several survey methods that utilize interviews. These are the personal or face-
to-face interview, the phone interview, and more recently, the online interview.
Advantages: Follow-up questions can be asked; provide better understanding of the answers of
the respondents
Disadvantages: Time-consuming; many target respondents have no public-listed phone
numbers or no telephones at all
1. Cross-Sectional Surveys
Collecting information from the respondents at a single period in time uses the cross-sectional type of
survey. Cross-sectional surveys usually utilize questionnaires to ask about a particular topic at one
point in time. For instance, a researcher conducted a cross-sectional survey asking teenagers’ views on
cigarette smoking as of May 2010. Sometimes, cross-sectional surveys are used to identify the
relationship between two variables, as in a comparative study. An example of this is administering a
cross-sectional survey about the relationship of peer pressure and cigarette smoking among teenagers
as of May 2010.
2. Longitudinal Surveys
When the researcher attempts to gather information over a period of time or from one point in time up
to another, he is doing a longitudinal survey. The aim of longitudinal surveys is to collect data and
examine the changes in the data gathered. Longitudinal surveys are used in cohort studies, panel
studies and trend studies.
Measurement Scales
1) Dichotomous Scales
A dichotomous scale is a two-point scale which presents options that are absolutely opposite each
other. This type of response scale does not give the respondent an opportunity to be neutral on his
answer in a question.
Examples:
Yes- No
True - False
Fair - Unfair
Agree – Disagree
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2) Rating Scales
Three-point, five-point, and seven-point scales are all included in the umbrella term “rating scale”. A
rating scale provides more than two options, in which the respondent can answer in neutrality over a
question being asked.
Examples:
1. Three-point Scales
Good - Fair – Poor
Agree – Undecided - Disagree
Extremely- Moderately - Not at all
Too much - About right - Too little
3. Seven-point Scales
Exceptional – Excellent – Very Good – Good – Fair – Poor – Very Poor
Very satisfied - Moderately satisfied - Slightly satisfied – Neutral - Slightly dissatisfied -
Moderately Dissatisfied- Very dissatisfied
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the attitude, we must choose which end of the scale will be positive, and which will be negative. The
simplest way to do this is to assign the positive end of the scale to your attitude. For our example, we'll
make “desire to learn” positive, and “desire to get a degree” negative.
3) Write statements
Next, we will write statements that reflect positive and negative aspects of these areas. We’ve defined
“positive” to mean “that which agrees with my position,” and “negative” means “that which disagrees
with my position.” The statements, even though reflecting subjective variables, should be objective.
That is, statements must not be systematically biased toward one position or the other. Students who
really want merely to get a degree should have no trouble scoring low on the scale. They should tend to
agree with statements reflecting “degree” and tend to disagree with statements reflecting “learning.” In
the same way, students who really want to learn should tend to agree with “learning” statements, and
tend to disagree with “degree” statements.
Rank
Rank order the evaluated items on clarity and potency. Choose an equal number of positive and
negative items from the best statements.
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The person who “strongly agrees” with a negative statement gets the minimum number of points (1),
while the one who “strongly disagrees” with a negative statement gets the maximum points (4). In our
four-point example, the scoring for negative
statements would be as follows: SD=4, D=3, A=2, and SA=1.
In this short 8-item example attitude scale subject attitude scores will range from a low of “8” (8 x 1 =
8) to a high of “32” (8 x 4 = 32). For a twenty-five item scale, this procedure yields scores ranging from
25 to 100. These scores can then be used to compare groups on the defined attitude
Reliability:
a. Will the measure employed repeatedly on the same individuals yield similar results? (stability)
b. Will the measure employed by different investigators yield similar results? (equivalence)
c. Will a set of different operational definitions of the same concept employed on the same individuals,
using the same data-collecting technique, yield a highly correlated result? Or, will all items of the
measure be internally consistent? (homogeneity) Reliability can be thought of as consistency. Does the
instrument consistently measure what it is intended to measure? It is not possible to calculate
reliability; however, there are four general estimators that you may encounter in reading research:
1. Inter-Rater/Observer Reliability: The degree to which different raters/observers give consistent
answers or estimates.
2. Test-Retest Reliability: The consistency of a measure evaluated over time.
3. Parallel-Forms Reliability: The reliability of two tests constructed the same way, from the same
content.
4. Internal Consistency Reliability: The consistency of results across items, often measured with
Cronbach’s Alpha.
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such as leadership capability, altruism, and civic involvement. The combination of these aspects,
alongside the SAT, is a more valid measure of the applicant’s potential for graduation, later social
involvement, and generosity (alumni giving) toward the alma mater.
Finally, the most useful instrument is both valid and reliable. Proponents of the SAT argue that it is
both. It is a moderately reliable predictor of future success and a moderately valid measure of a
student’s knowledge in Mathematics, Critical Reading, and Writing.
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UNIT 4
DATA ANALYSIS
Hypothesis Testing
Hypothesis can be referred to as the interpretation of certain facts which is just a possible solution or a
tentative answer to a problem and is completely or partly unverified in nature. Then afterwards on its
establishment, it ceases to be a hypothesis and then finally becomes a theory or a principle. The word
‘Hypothesis’ has come from the Greek word hypo (means under)and tithenas (means to place) together
these words indicate towards the support they provide to each other on the placement of the
hypothesis under the evidence, which acts as a foundation.
In Reality
Type I Error
Reject H0 α = probability of Type I OK
Error
You should be familiar with type I and type II errors from your introductory course. It is important to
note that we want to set α before the experiment (a-priori) because the Type I error is the more
‘grevious’ error to make. The typical value of α is 0.05, establishing a 95% confidence level. For this
course we will assume α =0.05.
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A tabular relationship between truthfulness/falseness of the null hypothesis and outcomes of the test
can be seen in the table below:
Null Hypothesis is true Null hypothesis is false
Reject null hypothesis Type I ErrorFalse Positive Correct OutcomeTrue
Positive
Fail to reject null hypothesis Correct outcomeTrue Type II ErrorFalse Negative
Negative
Let’s look at some business related examples. In these examples I have reworded the null hypothesis,
so be careful on the cost assessment.
Null Hypothesis Type I Error / False Positive Type II Error / False Negative
Medicine A cures Disease (H0 true, but rejected as (H0 false, but accepted as
B false)Medicine A cures Disease true)Medicine A does not cure
B, but is rejected as false Disease B, but is accepted as
true
Cost Assessment Lost opportunity cost for Unexpected side effects (maybe
rejecting an effective drug that even death) for using a drug that
could cure Disease B is not effective
The cost ramifications in the medicine example are quite substantial, so additional testing would likely
be justified in order to minimize the impact of the type II error (using an ineffective drug) in our
example. However, the cost ramifications in the Display Ad example are quite small, for both the type I
and type II errors, so additional investment in addressing the type I and type II errors is probably not
worthwhile
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is applied both variable and attributes No parametric test exist for Nominal scale data .Non parametric
test do exist for nominal and ordinal scale data Parametric test is powerful, if it exist It is not so
powerful like parametric test
6) Advantages of non parametric test: Non parametric test are simple and easy to understand∗ It will
not involve complicated sampling theory∗ No assumption is made regarding the parent population∗
This method is only available for nominal scale data∗ This method are easy applicable for attribute
dates.
7) Disadvantages of non parametric test: It can be applied only for nominal or ordinal scale∗ For any
problem, if any parametric test exist it is highly powerful.∗ Non parametric methods are not so efficient
as of parametric test∗ No nonparametric test available for testing the interactional analysis of variance
model.
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UNIT 5
CHI-SQUARE TEST
Purpose
1) The reason for doing an ANOVA is to see if there is any difference between groups on some variable.
2) For example, you might have data on student performance in non-assessed tutorial exercises as well
as their final grading. You are interested in seeing if tutorial performance is related to final grade.
ANOVA allows you to break up the group according to the grade and then see if performance is
different across these grades.
ANOVA is available for both parametric (score data) and non-parametric (ranking/ordering) data.
Types of ANOVA
One-way between groups
The example given above is called a one-way between groups model.
You are looking at the differences between the groups.
There is only one grouping (final grade) which you are using to define the groups.
This is the simplest version of ANOVA.
This type of ANOVA can also be used to compare variables between different groups - tutorial
performance from different intakes.
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statistics teach multivariate statistical analysis. This type of analysis is desirable because researchers
often hypothesize that a given outcome of interest is effected or influenced by more than one thing.
2) Multiple regression is not typically included under this heading, but can be thought of as a
multivariate analysis.
3) Commonly have many relevant variables in market research surveys
– E.g. one not atypical survey had ~2000 variables
– Typically researchers pore over many crosstabs
– However it can be difficult to make sense of these, and the crosstabs may be misleading
• MVA can help summarise the data
– E.g. factor analysis and segmentation based on agreement ratings on 20 attitude
statements
• MVA can also reduce the chance of obtaining spurious results
Multivariate Analysis Methods
• Two general types of MVA technique
– Analysis of dependence
• Where one (or more) variables are dependent variables, to be explained or
predicted by others
– E.g. Multiple regression, PLS, MDA
– Analysis of interdependence
• No variables thought of as “dependent”
• Look at the relationships among variables, objects or cases
– E.g. cluster analysis, factor analysis
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UNIT 6
REPORTING RESEARCH
Characteristics of a Research Report:
1. Information collected in the report must be relevant and focused to derive desired results.
Pictorial and graphical presentation of data and related information help to understand the details
easily. There is a possibility that the collected data in the report needs to be represented at many
places in different formats to fulfill the report goals. The ultimate goal is to determine all the issue
and make suitable strategies to cope up with these issue or problems.
2. Report should follow the exact predefined goals and objectives. If there is any sort of divergence
of related information which does not match the goals then the results are of no use. In fact there is
a probability of landing up in making negative or out of focus strategies, which will be very
dangerous.
3. The report should always contain the executive summary of the work. This is generally kept
before the actual report starts as it shows the summary of the desired business plan.
4. Apart from the actual analysis the report should also depict the reasons of making this report and
what advantages and profit it can provide after successful implementation of business plans
described inside the report.
5. It should also contain the methodology of the research which shows the overall process adopted
to create the report.
6. It is important that the report contains the possibility of errors in any of the module or process so
that immediate measures could be taken to cope up with these errors.
7. The report should contain the description of the questionnaires used in analysis and the way it
has been prepared.
8. The methodology used in the interviews should also be elaborated and what was achieved in this
should also be described.
9. If the information show that some aspects needs to predict the future trends then the reports
should depict that prediction. This prediction should have scale of success so that the accuracy
could be judged efficaciously. The report should also define each and every variable and element
used in creating these predictive analyses.
10. The report should be flexible enough to be changed accordingly. The analytical information
described inside the report should be maintained in such a way that there is no extra effort
labored if any strategy or process it to be changed in future. It should necessarily mould the
changes without changing the structure of the report.
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B.B.A. V Sem Subject- Research Methodology
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