This document discusses sampling methods used in research. It defines key terms like population, which refers to the entire group being studied, and sample, which is a subset of the population. Probability sampling methods aim to select a representative sample where every member of the population has an equal chance of being chosen. These include simple random sampling, systematic sampling, stratified sampling, and clustered sampling. Non-probability sampling methods do not use random selection and can include convenience sampling and judgment sampling. The document outlines different sampling techniques and discusses their merits like being economical and time-saving, but also notes potential demrits like sample error and personal bias.

1. SAMPLING
Dr. Urvashi Sharma
Department of Psychology
NIMS University, Jaipur

2. The entire group
from which a sample
is chosen is known
as the population.
(P. V. Young)
The sample is the
specific group of
individuals that will
be selected from the
target population.
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Dr. Urvashi Sharma, Assistant Professor
(Psychology)

3. POPULATION
 Population includes all sets of individuals, objects, or
reactions that can be described as having a unique
pattern of qualities.
 population can be defined in terms of geographical
location, age, income, and many other characteristics.
 It can be very broad or quite narrow: It may be infinite or
finite.
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

4. CONT…
 It is very important to define your target
population according to the purpose and
practicalities of your project.
 If the population is very large, demographically
mixed, and geographically dispersed, it might be
difficult to gain access to a representative
sample.
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

5. SAMPLE
 A sample refers to a representative group of target
population. It is smaller, manageable version of a
larger group and having the characteristics of a
larger populations. Samples are used in inferential
statistics and when population sizes are too large for
testing. A sample should represent the population as
a whole and not reflect any bias toward a specific
attribute.
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

6. SAMPLING FRAME
 The sampling frame is the actual list of
individuals that the sample will be drawn
from. Ideally, it should include the entire
target population.
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

7. SAMPLE SIZE
 The number of individuals in sample
depends on the size of the population, and
on how precisely you want the results to
represent the population as a whole.
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

8. Sampling
Census
Semi
probabilit
y
Probability
Non
probability
Parametric
method
Non
parametric
method
1/13/2021
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Dr. Urvashi Sharma, Assistant Professor
(Psychology)

9. PROBABILITY METHODS
 Probability sampling means that every member of the
population has a equal chance of being selected. In
this method we uses randomization to select the
sample.
 It is mainly used in quantitative data.
 If we want to produce results that are representative
of the whole population, we need to use a probability
sampling technique.
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

10. RANDOM SELECTION
 A random sample from a population is that
which consists of a group into which every
member of the population had an equal
chance of falling.
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

11. TYPES OF SAMPLING
 Probability Sampling Methods
1. Simple random sampling
2. Systematic sampling
3. Stratified sampling
4. Clustered sampling
Semi probability
sampling
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

12. CONT…
 Non-Probability Sampling Methods
 1. Convenience sampling
 2. Quota sampling
 3. Judgment (or Purposive) Sampling
 4. Snowball sampling
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

13. USE/MERITS OF SAMPLING METHOD
 Economical
 Time saving
 Reliable
 Conveniences
 Scientific
 Detailed accessibility
 Generalization
 Prediction
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

14. DEMERITS OF SAMPLING METHODS
 Problem of representative sample
 Knowledge about statistical techniques
 Need specialization
 Wrong prediction
 Sample error
 Personal bias
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Dr. Urvashi Sharma, Assistant
Professor (Psychology)

15. Dr. Urvashi Sharma, Assistant Professor
(Psychology)
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