Sampling is the process by which inference is made to the whole by
examining a part.
Purpose of sampling :
To provide various types of statistical information of a qualitative or
quantitative nature about the whole by examining a few selected
It is cheaper than census method.
It is economical too.
Probability sampling methods.
Non probability sampling methods.
It is a sampling technique in which the researcher divides the entire
target population into different subgroups, or strata, and then
randomly selects the final subjects proportionally from the different
This type of sampling is used when the researcher wants to highlight
specific subgroups within the population.
Cluster Sampling :
In cluster sampling the total population is divided into a number of
relatively small sub-divisions or groups which are themselves
clusters and then some of these cluster are randomly selected for
inclusion in the sample.
The purest form of probability sampling.
Assures each element in the population has an equal chance of being
included in the sample.
Systematic Sampling :
A method of selecting sample members from a larger population
according to a random starting point and a fixed, periodic
interval. Typically, every "nth" member is selected from the total
population for inclusion in the sample population.
Convenience sampling is a non-probability sampling technique
where samples are selected because of their convenient accessibility
and proximity to the researcher.
It is fast, inexpensive, easy and the subjects are readily available.
Judgement Sampling :
Judgmental sampling is a non-probability sampling technique where
the researcher selects units to be sampled based on their knowledge
and professional judgment.
This type of sampling technique is also known as purposive
sampling and authoritative sampling.
Snowball sampling is a non-probability sampling technique
that is used by researchers to identify potential subjects in
studies where subjects are hard to locate.
Quota Sampling :
Quota sampling is a non-probability sampling technique wherein the
assembled sample has the same proportions of individuals as the
entire population with respect to known characteristics, traits or
As quota sampling is not random so sampling method is biased and
lead to large sampling errors.
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