Exercise 12 Page 614

A bias is an error that results in a misrepresentation of a whole population.

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Every tenth employee who arrives at a company health fair answers a survey that asks for opinions about new health-related programs. Here, the population consists of all employees and the sample of every tenth employee surveyed. Let's recall how samples can be classified.

Name	Characteristic
Random Sample	Each member of the population has an equal chance of being selected.
Self-selected Sample	Members volunteer to be included in the sample.
Systematic Sample	Members are selected according to a specified interval from a random starting point.
Stratified Sample	The population is first divided into smaller groups that share a similar characteristic. Members are then randomly selected from each group.
Cluster Sample	The population is first divided into groups called clusters. All of the members in one or more of the clusters are selected.
Convenience Sample	Members that are readily available or easy to reach are selected.

Every tenth employee who arrives at a company health fair answers a survey. Therefore, this is systematic sample. Note that only employees who attend the company health fair are surveyed, however. These employees are more likely to have strong opinions about the new health-related programs. Therefore, we could conclude that the sample is biased.

Subchapter links

Communicate Your Answer p.609

Monitoring Progress p.611-613

Exercises p.614-616

Exercise 12 Page 614

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