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A bias in a sample is an error in sampling that results in misrepresentation of members of a population. Bias occurs when members of a population that are representing certain characteristics are more likely to be selected in a sample than others.
| Definition | |
|---|---|
| Unbiased Sample | A sample that is representative of the population. Conclusions drawn from this sample can be generalized to the whole population. |
| Biased Sample | A sample that overrepresents or underrepresents a certain part of the population. The inferences drawn based on this sample may be invalid. |
The chosen sampling method may either introduce or minimize a bias in a sample. The following real-life scenarios present examples of biased samples.
| Biased Sample | Explanation |
|---|---|
| A city council asks residents whether there should be an off-leash area for dogs in a park. A hundred dog owners are surveyed at the park. | The only people asked are dog owners. This means that respondents are more likely to have a strong opinion about an off-leash area for their dogs. |
| To assess the experiences of customers who shop online, a company e-mails purchasers with a link to a survey. | Because this sample is self-selected, only those who are very satisfied or dissatisfied with the shopping experience are likely to respond. |
| Every sixth boxer at a boxing camp is asked to name their favorite brand of boxing gloves. | Not all boxers go to a boxing camp, as camps are usually sponsored by a brand and take place in a single city. Also, professional boxers often organize their own private camps with hired sparring partners. |