2. Sampling
Prepared by
Dr. Manal Moussa

3. Outlines:
Introduction
Sampling terms
Types of Sampling
-Probability
1-Simple random sample
2-Stratified random sample
3-Cluster sampling
4-Systematic sampling
-Non- probability
1-Convenience sampling
2-Quota sampling
3-Purposive or judgmental sampling

4. Introduction:- The first two questions most researchers ask
once a research has been defined are '' how
many subjects will I need to complete my study?''
and '' how will I select them?''.

5. Sampling terms:-
Sampling: - is a process of selection a portion of
the population to obtain data regarding a problem.
Population: - is a group of subjects having
common characteristics. The population may
consist of events, animals, places, and individuals.
The target population: - is the population under
study which the researcher wants to generalize
the research findings.

6. Types of Sampling:-
There are two types of sampling probability & non-probability.
Probability sampling includes the following:-
1-Simple random sample.
2-Stratified random sample.
3-Cluster sampling.
4-Systematic sampling.

7. Non-probability sampling includes the following:-
1- Convenience sampling.
2- Purposive sampling.
3- Quota sampling.

8. Probability Sampling:-
Probability sampling: is a process of selecting
a representative sample of the target population.
Its purpose is to ensure that each element has an
equal, and independent.

9. *Four types of probability sampling designs are:-
1- Simple Random Sample:-
The simplest form of random sampling is called simple
random sample.
It is characterized by:-
An independent chance for each element to be selected
into the study.
A complete list of the accessible population.
A one-stage selection process. To start, the researcher
identifies the target population. Then list of all elements
of the target population (sampling frame), the next task is
randomly selected the participants.

10. Methods of collection:-
1-Placing the number in a bowl and drawing out the numbers one at time.
2-Using a table of random members.
3-Using a computer –generated selection of random members.

11. Advantages of simple random sampling:-
It eliminates researcher bias.
Require limited knowledge about population.
Provides a means for estimating sampling error.

12. Disadvantages of simple random sampling:-
A complete list of the accessible population is needed.
Very time consuming unless the computer is used to assist in the process.
Need a large sample size.

13. 2- Stratified Random Sampling:-
In stratified sampling, subjects are chosen so that certain
subgroups (two or more strata) in the target population
will be represented in the sample.
Strata are determined by mutually exclusive variables
such as gender, age, and educational level. After the
population divided, a simple random sample is taken
within each stratum.
It is used to ensure representatives of different groups
within the population.

14. Advantages of stratified random sample:-
Ensure the representation of a particular segment
of population.
Disadvantages of stratified random sample:-
It requires extensive knowledge of the population
under the study to stratify it accurately.
A complete list of a target population is needed.
It can be quickly but very complex and time
consuming.

15. 3- Systematic Sampling:-
It refers to a sampling strategy that involves the
selection of every case drawn from a population
list at fixed interval.
First; the listing the population must be random in
relation to the variable of interest .Systematic
random sampling can be conducted when an
ordered list of all members of the population is
available.

16. Second; the first element or member of the
sample must be selected randomly.
The sampling interval; is the standard
distance between the elements chosen for
the sample.

17. Advantages of systematic random sample:-
It is a fast, easy, and inexpensive way to draw a probability sample.
Its simplicity may be reducing error.

18. Disadvantages of systematic random sample:-
Not suitable in large or small number of population.
Some time we can't obtain required sample size.

19. 4- Cluster Sampling:-
In cluster sampling, a sampling frame is
developed that includes a list of all the states,
cities, institutions with which elements of the
identified population would be linked.

20. A randomized sample of these states, cities,
institutions, or organizations would then be used
in the study. In some cases, this randomized
selection continues through several stages and is
then referred to as '' multistage sampling''.

21. For ex. The researcher might first randomly
select states, then randomly select cities, within
the sample states, then randomly select hospitals
within selected cities, then randomly select the
patient on nursing unit who fit the criteria for the
study within selected hospitals.

22. Advantages of cluster sample:-
It is economical.
It is particularly when the population is large and geographically dispersed.

23. Disadvantages:-
More sampling errors tend to occur than other type of sampling.
The appropriate handling of the statistical data from cluster sampling is very complex.

24. Non-probability Sampling:-
Non-probability sampling; is an alternative
approach to probability sampling , because
random selection is not used, the sample may not
be representative of a large population , and thus
the results can't be generalized beyond the
sample study.

25. There are three types are:-
1- Convenience Sampling:-
Is the uses participant who are easily accessible
to the researcher and who meet the criteria of the
study.
For ex. Take all patient admitted in surgical
department with a particular diagnosis during this
month.

26. Advantages:-
It easier for researcher to obtain subjects.
Save in time and money.
Disadvantages:-
The potential for sampling bias.
The use of a sample that may not represent population.
The limited generalization of the results.

27. 2- Quota Sampling:-
Quota sampling is similar to stratified random
sampling in that participants are divided into strata based on specific characteristics to provide representativeness of different groups within the population.
Quota sampling differs from stratified random
sampling is that the participants are not randomly selected from each strata.

28. 3- Purposive or Judgmental Sampling:-
It involves the conscious selection by the
researcher of certain subjects or elements to
include the study.
A purposive sampling is used also when a highly
unusual group is being studied such as
a population with a rare genetic disease.
It used to describe lived experience of particular
phenomena (postpartum depression).

29. Advantages:-
Its allowance for the researcher to '' hand-pick''
the sample based on knowledge of the
phenomena of the study.

30. Disadvantages:-
The potential for sampling bias.
Uses of sample that dose not represent the population.
The very limited to generalization of results.