WHAT IS SAMPLING

1. PRESENTATION
ON
SAMPLING
Prepaired By:
Rajni Devi
M.A,M.LIB.SC,PGDCA(UGC NET)
Dept of Library & Information science
Kurukshetra University, Kurukshetra

2. SAMPLING

3. Introduction
Sampling method refers to the
collection of data from a few element of
the Population. Population refers to the
aggregate of data source. Any aggregate
from which data is collected is called a
population. A sample is a subset of
population.

4. Essential of Good Sampling
• Representative
• Adequacy
• Homogeneity
• Independent Ability
• Cost

5. Type of sampling
• Probability Sampling
• Non Probability Sampling

6. Type of sampling
Probability sampling
Simple random sampling
Systematic sampling
Stratified Random Sampling
Cluster Sampling
Sampling with probability proportional to
size
Sequential Sampling
Non Probability
sampling
Quota Sampling
Purposive or Judgement Sampling
Accidental Sampling
Snowball sampling

7. Probability Sampling
Probability sampling is also known
as random or chance sampling.
Under this sampling design, every
item of the population has an equal
chance of inclusion in the sample.

8. Types of Probability Sampling
• Simple random sampling
• Systematic sampling
• Stratified Random Sampling
• Cluster Sampling

9. Simple Random Sample
• Every subset of a specified size n from the
population has an equal chance of being
selected

10. Systematic Sample
• Every nth member ( for example: every 10th
person) is selected from a list of all population
members.

11. Stratified Random Sample
• The population is divided into two or more groups
called strata, according to some criterion, such as
geographic location, grade level, age, or income, and
subsamples are randomly selected from each strata.

12. 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.

13. Non Probability Sampling
Non probability sampling refers to the
sampling process in which the samples are
selected for a specific purpose with a pre-determined
basis of selection. This type of
sampling is also required at times when
random selection may be possible.

14. Non Probability Sampling
• Convenient Sampling
• Quota Sampling
• Purposive or Judgment Sampling
• Snowball sampling

15. Convenient Sampling
The sampling procedure of obtaining the
units that are most conveniently available.

16. Quota Sampling
In Quota Sampling, population is first
segmented into mutually exclusive sub-groups.
Then judgment is used to select the subjects or
units from each segment based on a specified
proportion.

17. Purposive or Judgment Sampling
Samples in which the selection criteria are
based on personal judgment that the element
is representative of the population under
study.

18. Snowball Sampling
Samples in which selection of additional
respondents is based on referrals from the
initial respondents.