A biased sample is one in which the method used
to create the sample results in samples that are systematically
different from the population.
For instance, consider a research project on attitudes
toward sex. Collecting the data by publishing a
questionnaire in a magazine and asking people to fill it out
and send it in would produce a biased sample. People
interested enough to spend their time and energy filling out
and sending in the questionnaire are likely to have
different attitudes toward sex than those not taking the
time to fill out the questionnaire.
It is important to realize that it
is the method used to create the sample not the actual make up of the
sample itself that defines the bias. A random sample that is very
different from the population is not biased: it is by
definition not systematically different from the population.
It is randomly different.