Explanation : Non-probability sampling is a sampling
technique which does not give all the
individuals in the population equal chances
of being selected, e.g.,
Convenience Sampling - selecting samples
that are accessible to the researcher or easy
to collect.
Consecutive sampling - selecting all
accessible subjects making the sample a
better representation of the entire population.
Judgmental Sampling or purposive sampling
- selecting with the belief that some subjects
are more suitable than other individuals for
the purpose.
Snowball Sampling - selecting a subject who
is asked to identify another potential subject
meeting the research criteria (Snowball
sample is hardly representative of the
population).
Quota Sampling - selecting sample
that ensures equal or proportionate
representation of subjects per trait considered
as basis of the quota for a given sample size.
Dimensional Sampling (an extension of
quota sampling) - the researcher takes
into account several characteristics (e.g.
gender, income, residence and education)
and ensures that there is at least one person
in the study representing each of the chosen
characteristics.
Probability sampling, on the other hand,
utilizes some form of random selection
method that ensures that the different units
in the population have equal probabilities of
being chosen, e.g.,
Simple Random Sampling - drawing a
name out of a lot, or using computers for
generating random numbers.
Stratified Random Sampling - randomly
selecting from smaller group divisions of a
large population that usually don't overlap
but represent the entire population together.
Cluster random sampling - randomly
selecting participants from selects areas
(Le. cities or counties) when they are
geographically spread out.
Systematic Sampling - randomly selecting
every ''nth'' individual to be a part of the
sample according to a random starting point
and a fixed periodic interval.