Sampling Issues What population is the survey investigating? While several restrictions
were placed on the demographics of the respondees, i.e. only Christian, the
voluntary nature of the eliciting process, along with the undefined nature of
the group to which the survey was advertised, makes delineation of a larger
population of interest intractable. As with the previous coin example, to be
able to make inferences about a larger group, we must understand the
relationship between the likelihood of making an observation and the nature of
the observation itself.
For example, if we wish to make inferences about the opinions of students
attending SPU, we need to come up with a sampling strategy through which we
can understand the relationship between sampling likelihood and sample
outcome. To avoid making extra work, one often would like a sampling scheme
such that the parameter estimates from the samples will be an unbiased
estimate of the population parameters. One such simple strategy is that of
simple random sampling. In this situation, there is an equal likelihood of
sampling from any given student at SPU. There are, of course, a range of
sampling strategies for a variety of situations.
Obtaining a representative sample may be difficult; if one were to go to an
institution and collect surveys from volunteers, one could run into a problem
in which people who volunteer and complete a survey do not have opinions which
are representative of the larger population. And one suspects that such could
be the case for the topics of Christian faith and evolution. (For example,
people with strong opinions may be more likely to volunteer to take a survey
than those with weak or conflicted opinions.) If, however, one could, with
uniform randomness, select a pool of students at an institution and elicit
their opinions, with a very low rate of refusal, then, one would be in a
position to make inferences about the larger group.
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 Contributed by: David Caccia
18ac
