Learn the process of Research. 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.

1. Research Process

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

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.

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.

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

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

41. Analysis of Data:

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

50. THANK YOU