1. SAMPLING METHODS AND
TECHNIQUES
PREPAIRED BY
MS. RAJNI BALA
M.LIB,M.PHIL.
DEPTT. OF LIBRARY & INFORMATION SCIENCE
KURUKSHETRA UNIVERSITY, KURUKSHETRA

2. KEY TERMS OF SAMPLING
 POPULATION
 SAMPLING
 SAMPLE
 QUALITIES OF GOOD SAMPLE
 TYPES OF SAMPLING
 PROBABILITY SAMPLING
 NON PROBABILITY SAMPLING

3. POPULATIO
All item in any field of inquiry is
called a population. It can be any
Institute, Group, Student, Company,
University library etc.

4. SAMPLING
 The process of selecting a sample from
a population using special sampling
techniques called sampling. It should be
ensured in the sampling process itself
that the sample selected is
representative of the population.

5. Sample
Sample is a small section of
population. The sampling is a
common activity in our day to
day work

6. SAMPLE VS. POPULATION
Population
Sample

7. DEFINITION OF SAMPLING
Sampling design in fact
means the joint processor to
selection and estimation. It
should be such error of
estimation is minimum

8. QUALITIES OF GOOD SAMPLING
 A Good Sample is true
 A good sample maintains accuracy.
 A good sample is comprehensive in nature
 A good sample free from bias.
 A good sample also economical
 The subjects of good sample are easily approachable
 A good sample makes the research work more feasible.
A good sample has the practicability for research situation.

10. TYPES OF SAMPLING
• . Probability sample – a method of sampling that
uses of random selection so that all units/ cases in the
population have an equal probability of being chosen.
• Non-probability sample – does not involve random
selection and methods are not based on the rationale of
probability theory.

11. TYPES OF PROBABILITY SAMPLING
 Simple Random Sampling
 Systematic Sampling
 Stratified Sampling
 Cluster Sampling
 Multi-Stage Sampling

12. SIMPLE RANDOMSAMPLING
Random selection is
a sampling method
in which each and
every item has an
equal chance of
selection.

13. SYSTEMATIC SAMPLING
 This is a selection method in which one or two
items are selected randomly, but other items are
selected by adding the average sampling interval to
the item selected randomly

14. STRATIFIED SAMPLING
 When the population is divided into different strata's
or groups and then samples are selected from each
stratum by simple random sampling procedure, we
call it as stratified random sampling

15. CLUSTER SAMPLE
 The population is divided into subgroups (clusters)
like families. A simple random sample is taken of
the subgroups and then all members of the cluster
selected are surveyed

16. MULTI-STAGE SAMPLING
Multistage refer to sampling plans where the
sampling is carried out in stages using
smaller and smaller sampling units at each
stage

17. TYPES OF NON-PROBABILITY SAMPLING
 1.Accidental Sampling
Accidental sampling is also based upon
convenience in accessing the sampling
population. In which involves the sample drawn
from that part of the population which is close to
hand.

18. 2.PURPOSIVE SAMPLING
We actually choose whom to involve in a
sample.
In purposive sampling, we sample with a
purpose in mind. We usually would have one
or more specific predefined groups we are
seeking.

19. Quota Sampling
In quota sampling, you select people non randomly
according to some fixed quota.
The population is divided into cells on the basis of
relevant control characteristics.
50 women, 50 men
The problem here (as in much purposive sampling)
is that we have to decide the specific characteristics
on which you will base the quota. Will it be by
gender, age, education race, religion, etc.?

20. Thanks