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Research Process
Research Process
 Research process consists of a series of actions or
  steps necessary to carry out research. It guides a
  researcher to conduct research in a planned and
  organized sequence.

 It is a procedure that is significant for a research to
  be accomplished within the constraints of time,
  cost and scope and for it to yield fruitful and
  timely results and conclusions.
Steps in the Research Process:
 The steps usually followed in the Research process
  are as following:

 Defining
               Reviewing        Hypothesis       Preparing
   the                                                          Collection
                   the                           Research
 Research                       Formulation                      of Data
               literature                         Design
 Problem




      Preparation of         Verification and
                                                   Analysis of Data
      Project Report        hypothesis testing
What is a Research Problem?


A research problem refers to
some      difficulty  which    a
researcher experiences in the
context of either a theoretical
or practical problem and wants
to obtain solution for the same.
Selecting the Problem
Some of the points observed by a
researcher in selecting a research
problem are:
•Overdone subjects should be avoided.
•Controversial subject should not chosen.
•Too narrow or too vague problems
should be avoided.
•Subject selected for research should be
familiar and feasible.
Necessity of Defining
         the problem
Defining the problem provides answers to
  many questions like:
• What data are to be collected?
• What characteristics of data are
  relevant and need to be studied?
• What relations are to be explored?
• What techniques are to be used for the
  purpose?
Techniques involved in
      defining the problem
1. Statement of problem in a general
   way.
2. Understanding the nature of the
   problem.
3. Surveying the available literature.
4. Developing the ideas through
   discussions.
5. Rephrasing the research problem.
Literature Review:
 A literature review is a body of text that aims to review
  the critical points of current knowledge including
  substantive findings as well as theoretical and
  methodological contributions to a particular topic.

 Literature reviews are secondary sources, and as such,
  do not report any new or original experimental work.

 It involves collecting the literature available from Books,
  Reports, which is relevant to your study. It usually
  precedes a research proposal and results section. Its
  ultimate goal is to bring the reader up to date with
  current literature on a topic and forms the basis for
  another goal, such as future research that may be
  needed in the area.
Formulating Hypothesis
• After extensive literature survey, researcher
  should state in clear terms the working
  hypothesis

  The role of the hypothesis is
   Guide the researcher by delimiting the area of
  research and to keep him on the right track.
   It sharpens his thinking and focuses attention
  on the more important facets of the problem.
   It also indicates the type of data required and
  the type of methods of data analysis to
  be used.
How does one go about developing working
 hypotheses?

(a) Discussions with colleagues and experts
(b) Examination of data and records, if available,
  concerning the problem for possible trends
(c) Review of similar studies in the area or of the
  studies on similar problems
(d) Exploratory personal investigation which
  involves original field interviews on a limited
  scale with interested parties
Preparing Research Design
  The function of research design is to provide
  for the collection of relevant evidence with
  minimal expenditure of effort, time and
  money
• The preparation of the research design,
  appropriate for a particular research
  problem, involves usually the consideration
  of the following:
• (i)the means of obtaining the information
• (ii)the availability and skills of the
  researcher and his staff (if any)
• (iii) explanation of the way in which selected
  means of obtaining information will be
  organised and the reasoning leading to the
  selection
• (iv) the time available for research
• (v)the cost factor relating to research, i.e.,
  the finance available for the purpose.
Methods of Sampling




Probability     Non Probability
Sampling          Sampling
Probability Sampling
• A probability sampling method is any method of sampling
  that utilizes some form of random selection.

• In probable sampling technique each sampling unit
  (household or individual) has a known probability of being
  included in the sample.


• Types of Probability Sampling :-
   1.   Simple Random Sampling.
   2.   Stratified random sampling
   3.   Cluster sampling
   4.   Systematic sampling
   5.   Multistage or Combination sampling
Random Sampling

• A sampling method in which all members of a
  group (population or universe) have an equal
  and independent chance of being selected.
Merits and Demerits of random sampling


      MERITS                 DEMERITS
  • Reduce the potential   • If population is
    for human bias.          heterogeneous, estimates
  • Allows us to make        have large variance
    generalizations
  • Readily available
Stratified Random Sampling

• The population is divided into groups
  (strata) and the data is collected from
  the strata by simple random sampling.
Merits and Demerits

      MERITS                    DEMERITS

• Each subdivision or   • Problems if strata are not
  strata can be           clearly defined.
  treated as a          • Analysis is (or can be)
  population.             quite complicated.
Cluster Sampling

 In Cluster Sampling a group of objects/Units for
  sampling is selected.

 A Cluster is a group of sampling units or elements,
  which can be identified, listed, and a sample of which
  can be chosen.
 One version of cluster sampling is area
  sampling or geographical cluster sampling. When
  the Clusters are selected on the basis of
  Geographical area, it is also called Area Sampling.
• In cluster sampling, we follow these steps:
1. Divide population into clusters (usually along
   geographic boundaries)
2. Randomly sample clusters
3. Measure all units within sampled clusters


• Advantage of Cluster Sampling:
1.    It is usually low cost oriented.
2.    It is convenient to Researcher.
•    Disadvantage:- Members of cluster tend to be
     similar –same socio-economic background, similar
     tastes, and buying behavior.
Systematic Sampling

• Here are the steps you need to follow in order to
  achieve a systematic random sample:
1. number the units in the population from 1 to N
2. decide on the n (sample size) that you want or need
3. k = N/n = the interval size
4. randomly select an integer between 1 to k
5. then take every kth unit.
Multistage Sampling
• In this type of Sampling combination of any two or
  more than two sampling methods is used, e.g.
  Combination of Cluster sampling and Stratified
  random (segment) sampling.
• Advantages
i.     cost and speed that the survey can be done in
ii.    convenience of finding the survey sample
iii.   normally more accurate than cluster sampling for the same
       size sample

• Disadvantages
i.     Is not as accurate as SRS if the sample is the same size
ii.    More testing is difficult to do
Non-probability Sampling
 Involves a process that does not give all the
  individuals in the population equal chances of
  being selected.

 not a product of a randomized selection processes.

 Subjects in a non-probability sample are usually
  selected on the basis of their accessibility or by the
  purposive personal judgment of the researcher.

 The downside of this is that an unknown proportion of
  the entire population is not sampled.
QUOTA

  TYPES
              JUDGEMENT
    OF
   NON
PROBABILITY   CONVENIENCE
 SAMPLING

               SNOWBALL
Quota Sampling
 A Quota sampling technique is one wherein the researcher
  ensures equal or proportionate representation of subjects
  depending on which trait is considered as basis of the quota.

 It basically selects a certain number of people from a certain
  group, for example, a certain no. of males and females.

 The bases of the quota are usually age, gender, education,
  race, religion and socioeconomic status.

 Quota sampling is the non probability version of stratified
  sampling.

 This method of selection is used in interview selections, product
  selections, marketing strategies and most elements of business
  running.
• ADVANTAGES                    • DISADVANTAGE
                                        S
• If a study aims to            • Limits your decisions.
  investigate a trait or a
  characteristic of a certain   • Does not allow much
  subgroup, this type of          variety.
  sampling is the ideal         • It is not possible to
  technique.                      assess sample error
• Quota Sampling also             as it is not random.
  allows the researchers to     • Biased sample.
  observe relationships
  between subgroups.
• It saves money and time.
Judgement Sampling

 A method of choosing a data sample drawn
  from a larger population based on one's own
  judgment, grounded in relevant experience.
 Judgment sampling is a common non-
  probability method. The researcher selects the
  sample based on judgment.
 Judgement sampling may curtail the
  generalisability of the finding due to the fact
  that we are using a sample of experts who are
  conveniently available to us.
 The advantages of Judgement
  sampling are:
i.     Low cost
ii.    Less time involved
iii.   A select number of people who are known to be
       related to the topic are part of the study which
       means that there are lesser chances of having
       people who will distort the data


 Some disadvantages are:
i.       It can be subject to researcher’s bias.
ii.    The group selected may not represent all the
       population
Convenience Sampling
 Convenience sampling is a non-probability sampling
  technique where subjects are selected because of
  their convenience, accessibility and proximity to the
  researcher.

 Many researchers prefer this sampling technique
  because it is fast, inexpensive, easy and the
  subjects are readily available.

 For Example, a sample obtained from automobile
  registrations, telephone directories etc. is
  convenience sampling.
Uses Of Convenience sampling

 • Easy to use
 • Helps the researcher to obtain basic data
   and trends regarding his study.
 • Useful in documenting a particular quality of
   a substance or phenomenon that occurs
   within a given sample.
 • Useful for detecting relationships among
   different phenomena.
Criticism of Convenience
               Sampling
• Sampling bias.

• Limitation in generalization and inference
  making about the entire population.

• Since the sample is not representative of
  the population, the results of the study
  cannot speak for the entire population.
  This results to a low external validity of the
  study.
Snowball Sampling

• Snowball sampling is a technique for
  getting a research sample where existing
  study subjects recruit future subjects from
  among their acquaintances.
• Thus the sample group appears to grow
  like a rolling snowball.
• This type of sampling is done where
  population is small and are selective.
• For Example : 1. Polo-players.
                  2. Owners of a particular
                      car brand.
How is Snowball Sampling
           done?
• The first step of snow ball sampling involves find
  your initial contacts or people among the target
  population whom you want to study.
• The initial contacts are then asked to refer more
  people (usually friends and acquaintances) who fit
  the study selection criteria.
• The contacts provided are then followed up, and
  the same cycle is repeated with these new people.
• This approach of requesting referrals is
  continuously repeated, until the targeted sample
  size is reached or a level of saturation is reached.
• A level of saturation means that no more new
  contacts can be generated and the cycle of
  referrals ends.
Criticism of Snowball Sampling

• Because sample members are not
  selected from a sampling frame, snowball
  samples are subject to numerous biases.
• For example, people who have many
  friends are more likely to be recruited into
  the sample. This introduces a selection
  bias in the sample selection and the
  sample is suggested to be not
  representative of all segments of
  population under study.
Collection of Data:
 Data collection is the process of gathering and measuring
  information on variables of interest, in an established systematic
  fashion that enables one to answer stated research questions, test
  hypotheses, and evaluate outcomes.

 The data collection component of research is common to all fields
  of study including physical and social sciences, humanities,
  business, etc. While methods vary by discipline, the emphasis on
  ensuring accurate and honest collection remains the same.

   Research Design outlines:
   How much Data is to be collected,
   What kind of Data is to collected: primary or secondary or both.
   Modes of Data collection.
Modes of Collection of Data:
• The various methods of collection of data are as
  following:
                                        Data




                 Primary                                  Secondary



                                                                      In - Depth
 Experiment                 Survey             Observation
                                                                      Techniques



                       Mail, Telephonic,                      Focus Groups, Panels, In-
 Lab, Field or                                 Obtrusive or
                     Personal Interview or                      depth Interviews and
  Web Based                                    unobtrusive
                            online                             Projection Techniques
Analysis of Data:
Analysis of Data:
• Analysis of data is a process of inspecting, cleaning,
  transforming, and modeling data with the goal of
  highlighting useful information, suggesting
  conclusions, and supporting decision making.

• Data analysis has multiple facets and approaches,
  encompassing diverse techniques under a variety of
  names, in different business, science, and social science
  domains.

• Data Analysis includes Data Cleaning, Grouping and
  Tabulation, Cross Tabulation, Graphical and
  Diagrammatic Presentation of Data, Use of Statistical
  Tools and Techniques on the classified data, etc
Data Analysis: Process
              • Removing erroneous data
   Data       • Checking data consistency
 Cleaning



             • Checking data Quality using Statistical and other methods
             • Analysis of extreme and missing observations
Initial Data • Comparison and correction of differences in coding schemes
 Analysis



              • Exploratory or Confirmatory Approach
Main Data     • Use of Higher Statistical and Analytical Techniques
Analysis
Hypothesis - testing

    After analyzing the data , the
researcher is in a position to test the
      hypothesis , if any , he had
          formulated earlier.
 Hypothesis testing will either result
in either accepting the hypothesis or
             in rejecting it.
Various methods for hypothesis
             testing

• Chi square test : to find out wheather the
  categorical data are independent or are
  dependent on each other.
• T-test : To find out wheather or not two
  independent data have different mean
  values on some measure .
• F-test : It is designed to test if variances of
  two different data are equal or not .
• ANOVA : analysis of variance.
• ANOCOVA : analysis of co-variance.
• In addition , the hypothesis may be
  tested through the use of one or more of
  such tests , depending upon the nature
  and object of research inquiry.
• If a hypothesis is tested and upheld
  several times , it may be possible for the
  researcher to arrive at generalisation i.e
  to build a theory.
Research Report:
• After the hypothesis testing and data verification, the
  Research report is prepared, which includes the following
  chapters:
                Executive Summary
                 Table of Contents
                   Introduction
                Research Objectives
               Research Methodology
                      Analysis
                      Findings
                    Limitations
                    Suggestions
                   Bibliography
Bibliography:


     Research Methods
     in Management
     • C.R. Kothari




      www.wikipedia.com
Presented By:
                 Mohita


      Aditi                  Bhawna




Anshuma                           Akshita




      Kavita                 Khushbu


               Bhagyashree
THANK YOU

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Research Process: Key Steps and Sampling Techniques

  • 2. Research Process  Research process consists of a series of actions or steps necessary to carry out research. It guides a researcher to conduct research in a planned and organized sequence.  It is a procedure that is significant for a research to be accomplished within the constraints of time, cost and scope and for it to yield fruitful and timely results and conclusions.
  • 3. Steps in the Research Process:  The steps usually followed in the Research process are as following: Defining Reviewing Hypothesis Preparing the Collection the Research Research Formulation of Data literature Design Problem Preparation of Verification and Analysis of Data Project Report hypothesis testing
  • 4.
  • 5. What is a Research Problem? A research problem refers to some difficulty which a researcher experiences in the context of either a theoretical or practical problem and wants to obtain solution for the same.
  • 6. Selecting the Problem Some of the points observed by a researcher in selecting a research problem are: •Overdone subjects should be avoided. •Controversial subject should not chosen. •Too narrow or too vague problems should be avoided. •Subject selected for research should be familiar and feasible.
  • 7. Necessity of Defining the problem Defining the problem provides answers to many questions like: • What data are to be collected? • What characteristics of data are relevant and need to be studied? • What relations are to be explored? • What techniques are to be used for the purpose?
  • 8. Techniques involved in defining the problem 1. Statement of problem in a general way. 2. Understanding the nature of the problem. 3. Surveying the available literature. 4. Developing the ideas through discussions. 5. Rephrasing the research problem.
  • 9. Literature Review:  A literature review is a body of text that aims to review the critical points of current knowledge including substantive findings as well as theoretical and methodological contributions to a particular topic.  Literature reviews are secondary sources, and as such, do not report any new or original experimental work.  It involves collecting the literature available from Books, Reports, which is relevant to your study. It usually precedes a research proposal and results section. Its ultimate goal is to bring the reader up to date with current literature on a topic and forms the basis for another goal, such as future research that may be needed in the area.
  • 10. Formulating Hypothesis • After extensive literature survey, researcher should state in clear terms the working hypothesis The role of the hypothesis is Guide the researcher by delimiting the area of research and to keep him on the right track. It sharpens his thinking and focuses attention on the more important facets of the problem. It also indicates the type of data required and the type of methods of data analysis to be used.
  • 11. How does one go about developing working hypotheses? (a) Discussions with colleagues and experts (b) Examination of data and records, if available, concerning the problem for possible trends (c) Review of similar studies in the area or of the studies on similar problems (d) Exploratory personal investigation which involves original field interviews on a limited scale with interested parties
  • 12. Preparing Research Design The function of research design is to provide for the collection of relevant evidence with minimal expenditure of effort, time and money • The preparation of the research design, appropriate for a particular research problem, involves usually the consideration of the following: • (i)the means of obtaining the information • (ii)the availability and skills of the researcher and his staff (if any)
  • 13. • (iii) explanation of the way in which selected means of obtaining information will be organised and the reasoning leading to the selection • (iv) the time available for research • (v)the cost factor relating to research, i.e., the finance available for the purpose.
  • 14.
  • 15. Methods of Sampling Probability Non Probability Sampling Sampling
  • 16. Probability Sampling • A probability sampling method is any method of sampling that utilizes some form of random selection. • In probable sampling technique each sampling unit (household or individual) has a known probability of being included in the sample. • Types of Probability Sampling :- 1. Simple Random Sampling. 2. Stratified random sampling 3. Cluster sampling 4. Systematic sampling 5. Multistage or Combination sampling
  • 17. Random Sampling • A sampling method in which all members of a group (population or universe) have an equal and independent chance of being selected.
  • 18. Merits and Demerits of random sampling MERITS DEMERITS • Reduce the potential • If population is for human bias. heterogeneous, estimates • Allows us to make have large variance generalizations • Readily available
  • 19. Stratified Random Sampling • The population is divided into groups (strata) and the data is collected from the strata by simple random sampling.
  • 20. Merits and Demerits MERITS DEMERITS • Each subdivision or • Problems if strata are not strata can be clearly defined. treated as a • Analysis is (or can be) population. quite complicated.
  • 21. Cluster Sampling  In Cluster Sampling a group of objects/Units for sampling is selected.  A Cluster is a group of sampling units or elements, which can be identified, listed, and a sample of which can be chosen.  One version of cluster sampling is area sampling or geographical cluster sampling. When the Clusters are selected on the basis of Geographical area, it is also called Area Sampling.
  • 22. • In cluster sampling, we follow these steps: 1. Divide population into clusters (usually along geographic boundaries) 2. Randomly sample clusters 3. Measure all units within sampled clusters • Advantage of Cluster Sampling: 1. It is usually low cost oriented. 2. It is convenient to Researcher. • Disadvantage:- Members of cluster tend to be similar –same socio-economic background, similar tastes, and buying behavior.
  • 23. Systematic Sampling • Here are the steps you need to follow in order to achieve a systematic random sample: 1. number the units in the population from 1 to N 2. decide on the n (sample size) that you want or need 3. k = N/n = the interval size 4. randomly select an integer between 1 to k 5. then take every kth unit.
  • 24.
  • 25. Multistage Sampling • In this type of Sampling combination of any two or more than two sampling methods is used, e.g. Combination of Cluster sampling and Stratified random (segment) sampling. • Advantages i. cost and speed that the survey can be done in ii. convenience of finding the survey sample iii. normally more accurate than cluster sampling for the same size sample • Disadvantages i. Is not as accurate as SRS if the sample is the same size ii. More testing is difficult to do
  • 26.
  • 27. Non-probability Sampling  Involves a process that does not give all the individuals in the population equal chances of being selected.  not a product of a randomized selection processes.  Subjects in a non-probability sample are usually selected on the basis of their accessibility or by the purposive personal judgment of the researcher.  The downside of this is that an unknown proportion of the entire population is not sampled.
  • 28. QUOTA TYPES JUDGEMENT OF NON PROBABILITY CONVENIENCE SAMPLING SNOWBALL
  • 29. Quota Sampling  A Quota sampling technique is one wherein the researcher ensures equal or proportionate representation of subjects depending on which trait is considered as basis of the quota.  It basically selects a certain number of people from a certain group, for example, a certain no. of males and females.  The bases of the quota are usually age, gender, education, race, religion and socioeconomic status.  Quota sampling is the non probability version of stratified sampling.  This method of selection is used in interview selections, product selections, marketing strategies and most elements of business running.
  • 30. • ADVANTAGES • DISADVANTAGE S • If a study aims to • Limits your decisions. investigate a trait or a characteristic of a certain • Does not allow much subgroup, this type of variety. sampling is the ideal • It is not possible to technique. assess sample error • Quota Sampling also as it is not random. allows the researchers to • Biased sample. observe relationships between subgroups. • It saves money and time.
  • 31. Judgement Sampling  A method of choosing a data sample drawn from a larger population based on one's own judgment, grounded in relevant experience.  Judgment sampling is a common non- probability method. The researcher selects the sample based on judgment.  Judgement sampling may curtail the generalisability of the finding due to the fact that we are using a sample of experts who are conveniently available to us.
  • 32.  The advantages of Judgement sampling are: i. Low cost ii. Less time involved iii. A select number of people who are known to be related to the topic are part of the study which means that there are lesser chances of having people who will distort the data  Some disadvantages are: i. It can be subject to researcher’s bias. ii. The group selected may not represent all the population
  • 33. Convenience Sampling  Convenience sampling is a non-probability sampling technique where subjects are selected because of their convenience, accessibility and proximity to the researcher.  Many researchers prefer this sampling technique because it is fast, inexpensive, easy and the subjects are readily available.  For Example, a sample obtained from automobile registrations, telephone directories etc. is convenience sampling.
  • 34. Uses Of Convenience sampling • Easy to use • Helps the researcher to obtain basic data and trends regarding his study. • Useful in documenting a particular quality of a substance or phenomenon that occurs within a given sample. • Useful for detecting relationships among different phenomena.
  • 35. Criticism of Convenience Sampling • Sampling bias. • Limitation in generalization and inference making about the entire population. • Since the sample is not representative of the population, the results of the study cannot speak for the entire population. This results to a low external validity of the study.
  • 36. Snowball Sampling • Snowball sampling is a technique for getting a research sample where existing study subjects recruit future subjects from among their acquaintances. • Thus the sample group appears to grow like a rolling snowball. • This type of sampling is done where population is small and are selective. • For Example : 1. Polo-players. 2. Owners of a particular car brand.
  • 37. How is Snowball Sampling done? • The first step of snow ball sampling involves find your initial contacts or people among the target population whom you want to study. • The initial contacts are then asked to refer more people (usually friends and acquaintances) who fit the study selection criteria. • The contacts provided are then followed up, and the same cycle is repeated with these new people. • This approach of requesting referrals is continuously repeated, until the targeted sample size is reached or a level of saturation is reached. • A level of saturation means that no more new contacts can be generated and the cycle of referrals ends.
  • 38. Criticism of Snowball Sampling • Because sample members are not selected from a sampling frame, snowball samples are subject to numerous biases. • For example, people who have many friends are more likely to be recruited into the sample. This introduces a selection bias in the sample selection and the sample is suggested to be not representative of all segments of population under study.
  • 39. Collection of Data:  Data collection is the process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes.  The data collection component of research is common to all fields of study including physical and social sciences, humanities, business, etc. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same.  Research Design outlines:  How much Data is to be collected,  What kind of Data is to collected: primary or secondary or both.  Modes of Data collection.
  • 40. Modes of Collection of Data: • The various methods of collection of data are as following: Data Primary Secondary In - Depth Experiment Survey Observation Techniques Mail, Telephonic, Focus Groups, Panels, In- Lab, Field or Obtrusive or Personal Interview or depth Interviews and Web Based unobtrusive online Projection Techniques
  • 42. Analysis of Data: • Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. • Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains. • Data Analysis includes Data Cleaning, Grouping and Tabulation, Cross Tabulation, Graphical and Diagrammatic Presentation of Data, Use of Statistical Tools and Techniques on the classified data, etc
  • 43. Data Analysis: Process • Removing erroneous data Data • Checking data consistency Cleaning • Checking data Quality using Statistical and other methods • Analysis of extreme and missing observations Initial Data • Comparison and correction of differences in coding schemes Analysis • Exploratory or Confirmatory Approach Main Data • Use of Higher Statistical and Analytical Techniques Analysis
  • 44. Hypothesis - testing After analyzing the data , the researcher is in a position to test the hypothesis , if any , he had formulated earlier. Hypothesis testing will either result in either accepting the hypothesis or in rejecting it.
  • 45. Various methods for hypothesis testing • Chi square test : to find out wheather the categorical data are independent or are dependent on each other. • T-test : To find out wheather or not two independent data have different mean values on some measure . • F-test : It is designed to test if variances of two different data are equal or not . • ANOVA : analysis of variance. • ANOCOVA : analysis of co-variance.
  • 46. • In addition , the hypothesis may be tested through the use of one or more of such tests , depending upon the nature and object of research inquiry. • If a hypothesis is tested and upheld several times , it may be possible for the researcher to arrive at generalisation i.e to build a theory.
  • 47. Research Report: • After the hypothesis testing and data verification, the Research report is prepared, which includes the following chapters: Executive Summary Table of Contents Introduction Research Objectives Research Methodology Analysis Findings Limitations Suggestions Bibliography
  • 48. Bibliography: Research Methods in Management • C.R. Kothari www.wikipedia.com
  • 49. Presented By: Mohita Aditi Bhawna Anshuma Akshita Kavita Khushbu Bhagyashree