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Each sampling method suffers from a form of bias. Identify the bias, tell how the sample statistic might deffer significantly from the population parameter, and suggest how the problem might be corrected. To gather feedback on his teaching, Professor Jones invites his students to visit his Web site and respond to a brief questionnaire. He is depressed to discover that 68% of those who respond are dissatisfied with his teaching.


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There are three types of bias:

Selection or undercoverage bias\textbf{Selection or undercoverage bias} will exclude part of the population.

Measurement or response bias\textbf{Measurement or response bias} will use a method that gives different values from the true value.

Nonresponse bias\textbf{Nonresponse bias} is the result of not having data for everybody in the sample.

We note that the people need to voluntarily respond to the questionnaire in order to be in the sample. The people who do not respond or do not go to the website then have no chance of being in the sample and thus a part of the population is excluded from the sample. This then implies that the sample suffers from selection or undercoverage bias\textbf{selection or undercoverage bias}.

Moreover, people with the strongest opinions tend to voluntarily respond. Since there was a high percentage (68%) of dissatisfied people in the sample, we would expect the actual percentage of dissatisfied people to be lower (as we expect those with the most negative opinions to have responded in this case).

The problem could be correctly by giving all students the brief questionnaire during his last class and requesting all of them to fill it out anonymously before leaving the class.

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