This document discusses sampling techniques used in scientific studies. It defines sampling as selecting a representative subset of a population to make inferences about the entire population. The key points are: 1) Sampling can save time and money compared to a census by studying a representative sample rather than the entire population. 2) Important principles of sampling include choosing samples systematically and objectively, clearly defining sample units, ensuring sample units are independent, and using consistent sampling methods. 3) There are various sampling techniques including simple random sampling, stratified random sampling, cluster sampling, and systematic random sampling. Each technique has advantages and limitations depending on the characteristics of the population and goals of the study.

1. Sampling
Dr Vinodh Kumar O.R
Division of Epidemiology
ICAR-Indian Veterinary Research Institute
Izatnagar, Bareilly-243 122

2. • Scientific method of data collection.
• Procedure by which some members of the population
are selected as representatives of the entire
population
Sampling

3. What is the need for sample ?
• Sampling can save time
and money.
• A sample study is usually
less expensive than a
census study.
• Selecting a representative
part of a population for
the purpose of
determining
characteristics of the
population .

4. PRINCIPLES OF SAMPLING
• Sample units must be chosen in a systematic and
objective manner.
• Sample units must be clearly defined and easily
identifiable.
• Sample units must be independent of each other.
• Same units of sample should be used throughout the
study.
• The selection process should be based on sound
criteria and should avoid Errors, bias and distortions.

5. • Selection (sampling) process,
which describes the method as
to how some units from the
population are included in the
sample.
• Estimation of precision i.e.
deviation of sample estimates
(means and standard
deviations).
Sampling involves two important
processes

6. Who is the group for
the study?
This is called the
study population
Who in the target
group should be
surveyed?
This is called the
sample.
How many people
should be surveyed?
This is called the
sample size.
How should the
people to be surveyed
by selected?
This is called the
sampling method/design

7. Definition of sampling terms
• Sampling unit (BSU)
• Elementary unit that will be
sampled.
• People
• Health care workers
• Hospitals
• Sampling frame
• List of all sampling units in the
population.
• Sampling scheme
• Method used to select sampling
units from the sampling frame.

8. Sampling techniques

9. IN CENSUS METHODLOGY EACH AND EVERY ELEMENT OF THE UNIVERSE IS CONTACTED
WHEREAS IN SAMPLING METHODOLOGY FEW ELEMENTS ARE SELECTED FROM UNIVERSE
FOR THE RESEARCH.

10. Population Sample

11. Volunteer Sampling
Researcher
I’ll do it!
I’ll do it!
I’ll do it!
Researcher uses only people who volunteer to participate
in the research

12. Network/Snowball Sampling
Researcher
Researcher selects a few participants, who then suggests others
who may be willing to participate

13. Simple Random Sampling
2, 6, 7, 12, 18Each member of the population is listed in fashion (e.g., numerically)
and then a sample is drawn by randomly selecting members of the population

14. SIMPLE RANDOM SAMPLE
• a) every member of the
population is equally likely to
be included in the sample
• b) the units in the sample are
selected independently of
each other.
• SRS is the gold standard for
sampling.
• In general, stratified random
sampling is more efficient
than simple random
sampling.

15. SRS advantages
1) Good representation – every
sample is equally likely to be
the one picked.
2) Unbiased – there is no
systematic sampling effort to
either underestimate or
overestimate the population
quantity of interest.
3) Sampling is completely
independent of the variable
being studied and of any
variables correlated with the
one of interest.

16. Stratified Random Sampling
Subgroups (“strata) created that separate members of the
population on some important attribute (e.g., sex, race).
A random sample from each stratum is then drawn.

17. Systematic/Sequential Random Sampling
Desired Sample Size: 5
Population Size: 20
Increment: 20/5 = 4
A random start in the sequence is selected, and sample is selected by
selecting cases sequentially in the list to produce the desired sample size
Random Start: 2

18. Cluster Sampling

19. • It will give us a larger variance, but sometimes we do out
of necessity.
• A good frame listing the population elements either is not
available or is very costly to obtain, whereas a frame
listing clusters is easily obtained.
• The cost of obtaining observations increases as the
distance separating the elements increases.
Why or When do we use cluster sampling?
How to obtain estimators of low variance in cluster sampling
• Clusters should be formed so that one cluster is similar to
another cluster.
• Each cluster should contain the full diversity of the population
and thus, is 'representative'.

20. Random Geographic Coordinate sampling
(RGCS)
• Offers a technique for the selection of random
sample without the need for a sampling frame.
• In RGCS two random numbers are selected, which
are x and y coordinate of a random point,
somewhere in the study area.
• Towns, Villages or herds that are located within a
certain distance (radius) from this random point are
identified.
• If there is more than one town , village or herd near
point , one is selected at random.
• Estimates are calculated according to weighted
proportions to the total number of herds within the
selection radius of that point

21. RCGS is useful mainly for the random
selection of groups such as villages or
herds.
Problems
RCGS is not suitable for selection of
Individual Animals
Sometimes randomly selected points
will contain no villages in specified
distance
Locating and counting the villages
requires much more travel , fields
costs are significantly higher

22. Random Geographic Coordinate sampling
(RGCS)

23. Need for representative sample of the population
Yes
Purpose of the study for
SRS
Systematic
Cluster
No
Purpose of the study
Obtain quick
information
Obtain
information
available only
with certain strata
of pop.Convenience
Sampling
Information that only
few respondents can
provide
Judgemental
Sampling
Need response from
particular strata of
pop.
Quota Sampling
Assessing different
parameters in various
strata of pop.
Is the size of all
strata equal
Yes No
Fixed
proportion
Stratified
sampling
Probability
proportion to
size Stratified
sampling
Generalization
when money is
limited
when elements are
listed in sequential
order