2. Survey Method
•A survey method is a process,
tool, or technique that you can use
to gather information in research
by asking questions to a
predefined group of people.
Typically, it facilitates the
exchange of information between
the research participants and the
person or organization carrying
3. Probability Sampling
Probability sampling is that a procedure is devised where
each person or item is given a known chance of inclusion
and the procedure is used for the selection of individuals.
is a sampling method that involves randomly selecting a
sample, or a part of the population that you want to
research. It is also sometimes called random sampling.
4. Types of Probability Sampling
•Simple random sampling
•Stratified sampling
•Systematic sampling
•Cluster sampling
5. Simple Random Sampling
• simple random sample gives every individual an equal chance of selection.
• Simple random sampling gathers a random
selection from the entire population, where
each unit has an equal chance of selection.
This is the most common way to select a
random sample.
6. Stratified sampling
• Stratified sampling collects a random selection of
a sample from within certain strata, or subgroups
within the population. Each subgroup is
separated from the others on the basis of a
common characteristic, such as gender, race, or
religion. This way, you can ensure that all
subgroups of a given population are adequately
represented within your sample population.
8. Cluster sampling
• Cluster sampling is the process of dividing the target population
into groups, called clusters. A randomly selected subsection of
these groups then forms your sample. Cluster sampling is an
efficient approach when you want to study large, geographically
dispersed populations. It usually involves existing groups that
are similar to each other in some way
2 types of cluster sampling
• Single (or one-stage) cluster sampling, when you divide the
entire population into clusters
• Multistage cluster sampling, when you divide the cluster further
into more clusters, in order to narrow down the sample size
9. Non-Probability Sampling
• Non-probability sampling is defined as a sampling
technique in which the researcher selects
samples based on the subjective judgment of the
researcher rather than random selection. It is a
less stringent method. This sampling method
depends heavily on the expertise of the
researchers. It is carried out by observation, and
researchers use it widely for qualitative research.
11. Quota sampling
• This is one of the most common forms of non-
probability sampling. Sampling is done until a
specific number of units (quotas) for various
subpopulations have been selected. Quota
sampling is a means for satisfying sample size
objectives for the subpopulations.
12. Judgmental Sampling
• Judgmental sampling, also called purposive sampling or
authoritative sampling, is a non-probability sampling
technique in which the sample members are chosen only
on the basis of the researcher’s knowledge and judgment.
As the researcher’s knowledge is instrumental in creating a
sample in this sampling technique, there are chances that
the results obtained will be highly accurate with a
minimum margin of error.
13. Snowball Sampling
• Snowball sampling is a non-probability sampling
method where new units are recruited by other units
to form part of the sample. Snowball sampling can be
a useful way to conduct research about people with
specific traits who might otherwise be difficult to
identify (e.g., people with a rare disease).
14. Convenience sampling
As the name suggests, a sample is selected on
the basis that it is easy to obtain and does the
job.
Convenience sampling offers a quick, low-
cost solution, but is particularly prone to bias.
15. Consecutive sampling
• Consecutive sampling is defined as a non-probability
sampling technique where samples are picked at the ease of a
researcher more like convenience sampling, only with a slight
variation. Here, the researcher selects a sample or group of
people, conducts research over a period, collects results, and
then moves on to another sample.
• This sampling technique gives the researcher a chance to work
with multiple samples to fine-tune his/her research work to
collect vital research insights.
