This document discusses various sampling techniques used in research. It defines sampling as selecting study units from a population. Probability sampling methods like simple random sampling, systematic sampling, stratified sampling and cluster sampling allow generalization to the population by giving units an equal chance of selection. Non-probability methods like convenience and quota sampling are used without a sampling frame. The document emphasizes the importance of representative, bias-free samples for research validity.

1. SAMPLING
TECHNIQUES
Dr.Yinka Adeniran, FMCPH
Lecturer/Consultant

2. LEARNING OBJECTIVES
At the end of this lecture, you should be able to:
■ Identify and describe the common methods
of sampling
■ Discuss problems of bias that should be
avoided when selecting a sample
■ Select the sampling method most
appropriate for the research design being
developed

3. SAMPLING
■ This is the selection of one or
more study units from a
defined study population.

4. Questions that need to be
answered:
■ What is the group of people (study population) from
which a sample is to be taken?
■ How many people need to be included in the
sample?
■ How will these people be selected?
An ideal sample should be representative of the
population from which it is drawn, i.e. it should have
all the major characteristics of that population

5. STUDY POPULATION
■ The study population should be clearly defined, e.g. according
to age, sex, and residence.
■ Each study population consists of study units. A study
population could consist of persons, villages, institutions,
records, equipment, etc.
Problem to be studied Study population Study unit
Immunisation coverage of
children 12-24 months of age in
Abakaliki
All children 12-24 months of age
in Abakaliki
One child 12-24 months of age in
Abakaliki
Environmental sanitation in
primary schools of Mushin, Lagos
All primary schools in Mushin One primary school in Mushin
Participation in the NHIS by
private health facilities inYaba
LCDA
All private health facilities in
Yaba LCDA
One private health facility in
Yaba LCDA

6. SAMPLING METHODS
1. Probability sampling methods
2. Non-probability sampling methods

7. Probability sampling methods
■ Simple random sampling
■ Systematic sampling
■ Stratified sampling
■ Cluster sampling
■ Multistage sampling

8. Non-probability sampling
methods
■ Convenience sampling
■ Quota sampling

9. NON-PROBABILITY
SAMPLING METHODS
■ The Sampling Frame is a listing of all the
study units that are contained within the
study population
■ If a sampling frame is not available, it is not
possible to sample the study units in such a
way that the probability for the different units
to be selected in the sample is known. In such
cases, non-probability sampling techniques
are used in taking a sample.

10. Convenience sampling
■ For the sake of convenience, the study units that
happen to be available at the time of data collection
are selected into the sample.
■ E.g. interview of all youths gathered at a street
viewing centre within Ilepa village, to determine the
attitude of teenagers in the village towardsVCT.
– More convenient than taking a random sample of the
teenagers in the village
– Gives a useful idea of their views
– However, sample may not be representative of the village
teenagers

11. Quota Sampling
■ This is a method that ensures the inclusion of a certain
number of sample units from different categories with
specific characteristics in the sample, so that the various
characteristics are represented.
■ In this method, the investigator includes as many people
in each category of study unit as he can find until that
quota is filled.
– E.g. inclusion of 20 patients each from different religious groups
in a study on attitudes towards family planning
– Useful when a convenience sample may not provide the desired
balance of study units.
– However, may still not be representative of the study
population

12. PROBABILITY SAMPLING
METHODS
■ These are used to select a sample when the aim of
the research is to measure variables and generalise
the findings obtained to the total study population.
■ They involve random selection procedures that
ensure that each unit of the sample is selected on
the basis of chance. All units of the population
should have an equal or a known chance of being
included in the sample.
■ Probability sampling methods require a listing of all
the study units within the population to be studied.
This list is referred to as the sampling frame.

13. Simple Random Sampling
■ The simplest form of probability sampling
Steps:
■ Make a numbered list of all the units in the population from
which the sample is to be drawn
■ Decide on the size of the sample
■ Select the required number of sampling units through one of
the following methods:
– Balloting
– Use of table of random numbers
■ E.g. a simple random sample of 50 primary school students
from a school population of 250

14. Systematic sampling
■ Study units are chosen at regular intervals from the
sampling frame.
■ The interval that is chosen for selection is called the
sampling interval.
■ The number of the first study unit to be chosen is
selected through simple random sampling, and then
the sampling interval is applied.
■ Sampling fraction = sample size/study population
– In the last example, that would be 50/250 = 1/5
– The sampling interval would therefore be 5

15. Systematic sampling (II)
Advantages:
■ Less time-consuming & easier to carry out than
simple random sampling.
Disadvantages:
■ Risk of bias – sampling interval may coincide with a
systematic variation in the study population

16. STRATIFIED SAMPLING
■ If it is important that the sample includes representation from
various groups of study units with specific characteristics, e.g.
residents from rural and urban areas, different classes in a
school, then the sampling frame must be divided into groups,
or strata, according to these characteristics.
■ Samples of a predetermined size are obtained from each
stratum within the study population using another probability
sampling method.
■ Stratified sampling is only possible when the proportions or
size of each strata that make up the study population are
known.
■ The sampling fraction for each of the strata could be the same,
i.e. proportionate, or could differ for each strata, i.e. non-
proportionate.

17. Stratified sampling (II)
Advantages:
■ Representation of various sub-groups or strata of
interest within the study population
Disadvantages:
■ Unequal sampling fractions may give a different
picture of the situation found from research, when
generalising to the study population.

18. Cluster Sampling
■ This is the selection of groups of study units (clusters)
instead of individual study units.
■ It is used:
– When a complete sampling frame does not exist
– Sampling units are scattered in groups across a very
large area
– The list of groupings of study units can be easily
compiled, e.g. villages, communities, schools
■ Clusters are often geographic units, e.g. villages,
communities, or organizational units, e.g. schools, clinics

19. Multistage sampling
■ A multistage sampling procedure is carried out in
stages or phases, and usually involves more than one
sampling method.
■ It is used for community-based studies, usually
involving large and diverse populations.

20. Advantages & disadvantages of
cluster and multistage sampling
methods
Advantages:
■ Less time-consuming & easier to carry out than simple random
sampling
■ A complete sampling frame for each study unit may not be
required
Disadvantages:
■ A larger probability that the sample will not be representative
of the total study population than in simple random sampling

21. BIAS IN SAMPLING
Bias in sampling is a systematic error in the
sampling procedure that leads to a distortion
in the results of the study
■ This is as a result of improper sampling procedures that result in
the sample not being representative of the study population
■ If probability sampling methods are properly employed, then an
important source of bias is non-response.
■ Non response may be due to absence of subjects, or from refusal
to respond or cooperate with the interviewer.
■ To reduce the effect of non-response, additional people may be
included in the sample during selection
■ It is important in any study to mention the non-response rate, and
to discuss how it might have affected the results.

22. Sources of bias in sampling
■ Non-response
■ Use of volunteers & other non-probability
sampling techniques
■ Seasonal bias
■ Selection of easily accessible areas as
opposed to relatively inaccessible ones