it will help the students of research and advance studies

1. Selecting a sample
CONTENTS
• Sampling defined
• Types of sampling
• Sampling in quantitative research
• Defining population
• Selection of random, stratified, cluster and systematic sampling
• Determining sample size
• sample error and Bias
• Non random sample
• Sampling in qualitative research
• Selecting research participants
• Determining sample size

2. Sampling defined
Certain individuals selected to represent a large
group in a study, from which they are selected

3. Types of sampling
• In quantitative research sample is not taken
from whole population but a few samples
represent the whole
• The selected sample from population must be
defined so as to represent the whole
population
• Selection must be a realistic choice i.e.
accessible

4. Sampling in quantitative research
• No data from entire population is taken in
quantitative research
• Sample from a few can be generalized over whole
population
• Sample must be correctly selected to procure fine
results
• Sample must be an adequate representation of
target population
• Sample may or may not be perfectly represent the
whole population

5. Defining population
• Population must be defined e.g. women
judges as family judges in sindh
• Chosen population must be realistic (existing)
• Narrow selection saves time of researcher
• Description of sample i.e. number and
qualification etc.

6. Selection of random and stratified sampling
 RANDOM SAMPLE:
• Random sampling selection must not be haphazard
• It must be feasible to the researcher
• Selection of random sampling depends upon
circumstances of each case differently
 STRATIFIED SAMPLING
• It is representation of subgroups in sampling
• It may be proportional
• Adequate samples be taken from each subgroup
• It may or may not be equal selection

7. Selection of cluster and systematic sampling
 CLUSTER SAMPLE:
• In cluster sampling, groups are taken as samples not
individuals
• It is done where list of all members is not easily available
to researcher
• Desired sampling must be determined
 SYSTEMATIC SAMPLING
• It is sampling where every 5th or 10th individual is
• it is not very often used but it may be feasible in some
cases

8. Determining sample size
• The less the population the more the sample
• If population in bulk then sample size may be
upto 20%
• For survey research the sample size may at
least 10% to 20%
• It is necessary that the sample size may
represent the population properly

9. Sample error and Bias
• There is no guarantee of error free in random sampling
• To avoid error or bias a large sample is needed
• A chance sampling is better to avoid error or bias
• The chance variation is called sampling error
• Bias is fault of the researcher
• Where directly samples are not taken but a
presumption is taken from other than samples is a type
of bias by the researcher
• Researcher should avoid the sources of bias
• If any bias is unavoidable than researcher should report
in his research

10. Sampling in qualitative research
• Samples in qualitative research are different, smaller
and less representative
• The aim and need in qualitative research is different
than that of quantitative one
• Selection of best sample participants for the purpose
of researcher is necessary
• The quality is to be considered in each thing while
selecting a sample

11. Selecting research participants
• Research participants must be purpose oriented
• The experience and insight of participants is
considered in qualitative research
• Communication of researcher with participants is
necessary
• It also include intensity sampling random purposive
sampling

12. Determining sample size
• There is no hard rule for number of participants
• Sample must be representative to the population size
• Some times a single participant is sufficient and on
the other hand it may be 50 to 70.

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