Sampling Method |
Definition |
Uses |
Limitations |
Cluster Sampling)
|
Units in the population can
often be found in certain geographic groups or "clusters"
(e.g. primary school children in Derbyshire. A random sample of
clusters is taken, then all units within the cluster are examined |
Quick & easy; does not
require complete population information; good for face-to-face surveys |
Expensive if the clusters are
large; greater risk of sampling error |
Convenience Sampling |
Uses those who are willing to
volunteer |
Readily available; large amount
of information can be gathered quickly |
Cannot extrapolate from sample
to infer about the population; prone to volunteer bias |
Judgement Sampling |
A deliberate choice of a sample
- the opposite of random |
Good for providing illustrative
examples or case studies |
Very prone to bias; samples
often small; cannot extrapolate from sample |
Quota Sampling |
Aim is to obtain a sample that
is "representative" of the overall population; the
population is divided ("stratified") by the most important
variables (e.g. income,. age, location) and a required quota sample is
drawn from each stratum |
Quick & easy way of
obtaining a sample |
Not random, so still some risk
of bias; need to undertand the population to be able to identify the
basis of stratification |
Simply Random Sampling |
Ensures that every member of
the population has an equal chance of slection |
Simply to design and interpret;
can calculate estimate of the population and the sampling error |
Need a complete and accurate
population listing; may not be practical if the sample requires lots
of small visits all over the country |
Systematic Sampling |
After randomly selecting a
starting point from the population, between 1 and "n",
every nth unit is selected, where n equals the
population size divided by the sample size |
Easier to extract the sample
than via simple random; ensures sample is spread across the population |
Can be costly and
time-consuming if the sample is not conveniently located |