The document discusses research design and methodology. It defines research design and outlines its key features and needs. It describes different types of research designs including exploratory, descriptive, diagnostic, and hypothesis testing. It also discusses sampling, including probability and non-probability sampling. Finally, it covers potential errors in surveys such as sampling errors and non-sampling errors.

2. RESEARCH DESIGN
A Team Work by
Nandani Shukla
Prashant Ranjan
Raman Kumar
Neeraj Pandey
Millind Awasthi

3. Index
• 1.Meaning of research design
• 2.Features of a good research
design
• 3.Needs of research design
• 4. Different research design
• 5. Sampling
• 6. types
• 7. Errors in Survey

4. Meaning of research design
1.Arrangements of conditions.
2.Overall framework of the projects.
3.Specific master plan or model.
4.Blueprint.
5.Guides the investigators.

5. Definition of research design
The research design refers to the overall strategy
that you choose to integrate the different
components of the study in a coherent and
logical way ,there by ,ensuring you will effectively
address the research problem .
It constitutes the blueprint for the collection ,
measurement and analysis of data.

6. The important features of a research design:
• The means of obtaining information.
• The availability and skills of the
researcher and staff,if any;
• The objective of the problem to be
studied.
• The nature of the problem.
• The availability of the time and money for
the research worker.
• The design should be accurate with
minimum bias in the accurate description.

7. Need For Research Design
• Research design is needed because it
facilitates the smooth sailing of the various
research operations ,thereby making research
as efficient as possible yielding maximal
information with minimal expenditure.
• The design helps the researcher to organize his
ideas in a form whereby it will be possible for
him to look for flaws and inadequacies.

8. Research design must contain:
• a clear statement of the research problem.
• procedures and techniques to be used for
gathering information.
• the population to be studied.
• methods to be used in processing and
analyzing data.

9. Different research designs:
1.Exploratory research studies Also termed as
formulative research studies-
▫ The main purpose: formulating a problem
for more precise investigation;
Developing the working hypotheses from an
operational point of view;
The major emphasis is on the discovery of
ideas and insights.

10. • ▫ Descriptive research studies describing the
characteristics of a particular individual, or of a group.
▫ Diagnostic research studies determine the frequency
with which something occurs or its association with
something else.
for example;
Finding the most frequent diseases that affects the
children of a town.The reader of the research will know
What to do to prevent that disease thus , more people
will live a healthy life.
2. Descriptive and diagnostic research
studies:

11. • 3. hypothesis-testingresearch studies:
• known as experimental studies or design of
experiments,tests the hypotheses of causal relationships
between variables.
• Usually experiments meet this requirement

12. SAMPLING DESIGN
The process of obtaining information from
a subset (sample) of a larger group
(population).
The results for the sample are then used
to make estimates of the larger group.
Faster and cheaper than asking the entire
population.

13. • Two keys for sample design:
1. Selecting the right people-
• Have to be selected scientifically so that they are
representative of the population
2. Selecting the right number of the right people-
• To minimize sampling errors I.e. choosing the wrong
people by chance

14. Sampling Design Process

15. Types of sampling design
• Probability sampling - equal chance of being included in the
sample (random)
-simple random sampling
-systematic sampling
-stratified sampling
-cluster sampling
• Non-probability sampling - unequal chance of being included
in the sample (non-random)
-convenience sampling
- judgement sampling
-snowball sampling
-quota sampling

16. Probability Vs. Non-probability sampling:
• Non-probability sampling is less time consuming
and less expensive.
• The probability of selecting one element over
another is not known and therefore the estimates
cannot be projected to the population with any
specified level of confidence. Quantitative
generalizations about population can only be done
under probability sampling.
• However, in practice, marketing researchers also
apply statistics to study non-probability samples.

17. Errors in survey
• Random Sampling Error
• random error- the sample selected is not
representative of the population due to
chance
• the level of it is controlled by sample size
• a larger sample size leads to a smaller
sampling error.

18. Sampling Errors
Sampling error is the error that arise in a data collection process
as a result Of taking sample from a population rather than
using a whole population.
Sampling
error
Population
specificati
on error
Selection
error
Non
Response
error
Sample
Frame
error

19. Population specification error
This error occurs when the researcher does not understand who
Should survey.
Sample Frame error
A frame error occurs when the wrong sub-population
Is used to select a sample.

20. Selection error
this occurs when respondents self select their
participation in The study – only those that are
interested respondent.
Selection error can be controlled by going
extra lengths to get participation .
Non-response error
Non response error occurs when respondents are
different than those Who do not respond.

21. Non-Sampling Errors (I)
• Non-sampling Error
-systematic Error
-the level of it is NOT controlled by sample size.
• The basic types of non-sampling error
-Non-response error
-Response or data error
• A non-response error occurs when units selected as part of the
sampling procedure do not respond in whole or in part.
-If non-respondents are not different from those that did respond,
there is no non-response error.

22. Non-Sampling Errors (II)
• A response or data error is any systematic bias
that occurs during data collection, analysis or
interpretation
-Respondent error (e.g., lying, forgetting, etc.)
-Interviewer bias
-Recording errors
-Poorly designed questionnaires