This document discusses sampling techniques in research methodology. It defines a population as the overall group being studied and sampling as selecting a subset of individuals from the population to collect data from. There are two main types of sampling: probability sampling, which uses random selection to choose participants so that all members of the population have an equal chance of being selected; and non-probability sampling, which does not rely on random selection and can result in more bias. Several examples of probability and non-probability sampling techniques are provided.

1. 29-01-2019

2. Objectives
 Students will be understanding the sample techniques
in research methodology.

3. Introduction
 Researchers commonly examine traits or
characteristics (parameters) of populations in their
studies. A population is a group of individual units
with some commonality. For example, a researcher
may want to study characteristics of female smokers in
Pakistan. This would be the population being analyzed
in the study, but it would be impossible to collect
information from all female smokers in Pakistan.

4.  Therefore, the researcher would select individuals
from which to collect the data. This is
called sampling. The group from which the data is
drawn is a representative sample of the population the
results of the study can be generalized to the
population as a whole.

5.  The sample will be representative of the population if
the researcher uses a random selection procedure to
choose participants. The group of units or individuals
who have a legitimate chance of being selected are
sometimes referred to as the sampling frame. If a
researcher studied developmental milestones of
preschool children and target licensed preschools to
collect the data, the sampling frame would be all
preschool aged children in those preschools.

6.  Students in those preschools could then be selected at
random through a systematic method to participate in
the study. This does, however, lead to a discussion
of biases in research. For example, low-income
children may be less likely to be enrolled in preschool
and therefore, may be excluded from the study. Extra
care has to be taken to control biases when
determining sampling techniques.

7.  There are two main types of sampling: probability and
non-probability sampling. The difference between the
two types is whether or not the sampling selection
involves randomization. Randomization occurs when
all members of the sampling frame have an equal
opportunity of being selected for the study. Following
is a discussion of probability and non-probability
sampling and the different types of each.

8. Probability Sampling
 Uses randomization and takes steps to ensure all
members of a population have a chance of being
selected. There are several variations on this type of
sampling and following is a list of ways probability
sampling may occur:
 Random sampling – every member has an equal
chance
 Stratified sampling – population divided into
subgroups (strata) and members are randomly
selected from each group

9.  Systematic sampling – uses a specific system to select
members such as every 10th person on an alphabetized
list
 Cluster random sampling – divides the population into
clusters, clusters are randomly selected and all
members of the cluster selected are sampled
 Multi-stage random sampling – a combination of one
or more of the above methods

10. Non-probability Sampling
 Does not rely on the use of randomization techniques
to select members. This is typically done in studies
where randomization is not possible in order to obtain
a representative sample. Bias is more of a concern with
this type of sampling. The different types of non-
probability sampling are as follows:

11.  Convenience or accidental sampling – members or
units are selected based on availability
 Purposive sampling – members of a particular group
are purposefully sought after
 Modal instance sampling – members or units are the
most common within a defined group and therefore
are sought after
 Expert sampling – members considered to be of high
quality are chosen for participation

12.  Proportional and non-proportional quota sampling –
members are sampled until exact proportions of
certain types of data are obtained or until sufficient
data in different categories is collected
 Diversity sampling – members are selected
intentionally across the possible types of responses to
capture all possibilities
 Snowball sampling – members are sampled and then
asked to help identify other members to sample and
this process continues until enough samples are
collected

13.  Thank You