Stratified random sampling is a type of probability sampling
technique [see our article Probability sampling if you do not
know what probability sampling is]. Unlike the simple random
sample and the systematic random sample, sometimes we are
interested in particular strata (meaning groups) within the
population (e.g., males vs. females; houses vs. apartments,
etc.) [see our article, Sampling: The basics, if you are unsure
about the terms unit, sample, strata and population]. With the
stratified random sample, there is an equal chance (probability)
of selecting each unit from within a particular stratum (group)
of the population when creating the sample. This article
explains (a) what stratified random sampling is, (b) how to
create a stratified random sample, and (c) the advantages and
disadvantages (limitations) of stratified random sampling.
Imagine that a researcher wants to understand more about the
career goals of students at the University of Bath. Let's say
that the university has roughly 10,000 studen