AN OVERVIEW OF SAMPLING
There are many ways to draw samples
from a population – and there are also
many ways that sampling can go awry.
We intuitively think of a good sample as
one that is representative of the population
from which the sample has been drawn. By
‘representative’ we do not necessarily mean
the sample matches the population in terms
of observable characteristics, but rather that
the results from the data we collect from
the sample are consistent with the results we
would have obtained if we had collected data
on the entire population.Of course, the phrase ‘consistent with’
is vague and, if this was an exposition of
the mathematics of sampling, would require
a precise definition. However, we will not
cover the details of survey sampling here.1
Rather, in this section we will describe the
various sampling methods and discuss the
main issues in characterizing the accuracy
of a survey, with a particular focus on
terminology and definitions, in order that
we can put the subsequent discussion about
Internet-based surveys in an appropriate
context.