representative. The danger in all nonprobability samples is that some (unknown) bias may affect the
degree to which the sample is representative. That isn’t to say that random samples can’t be
nonrepresentative, just that we have a better chance of avoiding bias. (Remember the difference!) Some
types of nonrandom sampling techniques that tend to be biased are:
• self-selected sample or voluntary response sample: People choose whether or not to participate in
the survey. A radio call-in show is a typical voluntary response sample.
• convenience sampling: The pollster obtains the sample any way he can, usually with the ease of
obtaining the sample in mind. For example, handing out questionnaires to every member of a given
class at school would be a convenience sample. The key issue here is that the surveyor makes the
decision whom to include in the sample.
• quota sampling: The pollster attempts to generate a representative sample by choosing sample
members based on matching individual characteristics to known characteristics of the population. This
is similar to a stratified random sample, only the process for selecting the sample is nonrandom.
Sampling Bias
We are trying to avoid bias in our sampling techniques, which would mean our method chooses samples
that produce estimates that are, on average, either too high or too low, which is the tendency for our
results to favor, systematically, one outcome over another.
Undercoverage
One type of sampling bias results from undercoverage . This happens when some part of the population
being sampled is somehow excluded. This can happen when the sampling frame (the list from which the
sample will be drawn) isn’t the same as the target population. It can also occur when part of the sample
selected fails to respond for some reason.
example: A pollster conducts a telephone survey to gather opinions of the general population
about welfare. Persons too poor to be able to afford a telephone are certainly interested in this
issue, but will be systematically excluded from the sample. The resulting sample will be
biased because of the exclusion of this group.Voluntary Response Bias
Voluntary response bias occurs with self-selected samples. Persons who feel most strongly about an
issue are most likely to respond. Nonresponse bias , the possible biases of those who choose not to
respond, is a related issue.
example: You decide to find out how your neighbors feel about the neighbor who seems to be
running a car repair shop on his front lawn. You place a questionnaire in every mailbox within
sight of the offending home and ask the people to fill it out and return it to you. About 1/2 of the
neighbors return the survey, and 95% of those who do say that they find the situation
intolerable. We have no way of knowing the feelings of the 50% of those who didn’t return the
survey—they may be perfectly happy with the “bad” neighbor. Those who have the strongest
opinions are those most likely to return your survey—and they may not represent the opinions
of all. Most likely they do not.
example: In response to a question once posed in Ann Landers’s advice column, some 70% of
respondents (almost 10,000 readers) wrote that they would choose not to have children if they