Sampling bias

In statistics, the word bias has divergent meanings. Some forms of statistical bias are very bad; others can have good effects in some cases; see bias (statistics).

A biased sample is one that is falsely taken to be typical of a population from which it is drawn. Someone saying "Everyone liked that movie!" might not mention that the "everyone" was them and three of their friends, or a group of the star's fans.

Online and call-in polls are particularly at risk of this error, because the respondents are self-selected. At best, this means the people who care most about an issue will answer; at worst, people listening to a particular radio host, or on a political mailing list, flood the poll.

Biased samples are not always an attempt to mislead: in 1936, in the early days of opinion polling, the American Literary Digest magazine called two million random telephone numbers, questioned the people who answered, and predicted the election result. They got it wrong because, at the time, telephones were far from universal, and telephone owners were not a good sample of the electorate as a whole. In contrast, a poll of only 50,000 citizens selected by George Gallup's organization successfully predicted the result, leading to the popularity of the Gallup poll.

Example

• According to a survey of delegates at the Communist Party Convention, the Communist Party is the most popular political party in the country.

Spotlight fallacy

Description: The Spotlight fallacy is committed when a person uncritically assumes that all members or cases of a certain class or type are like those that receive the most attention or coverage in the media. This line of “reasoning” has the following form:

1. Xs with quality Q receive a great deal of attention or coverage in the media. 2. Therefore all Xs have quality Q.

This line of reasoning is fallacious since the mere fact that someone or something attracts the most attention or coverage in the media does not mean that it automatically represents the whole population. For example, suppose a mass murderer from Old Town, Maine received a great deal of attention in the media. It would hardly follow that everyone from the town is a mass murderer.

The Spotlight fallacy derives its name from the fact that receiving a great deal of attention or coverage is often referred to as being in the spotlight. It is similar to Hasty Generalization, Biased Sample and Misleading Vividness because the error being made involves generalizing about a population based on an inadequate or flawed sample. The Spotlight Fallacy is a very common fallacy. This fallacy most often occurs when people assume that those who receive the most media attention actually represent the groups they belong to. For example, some people began to believe that all those who oppose abortion are willing to gun down doctors in cold blood simply because those incidents received a great deal of media attention. Since the media typically covers people or events that are unusual or exceptional, it is somewhat odd for people to believe that such people or events are representative.

Examples

1. I wouldn't like to go to America because of all the gun crime, we see it on the news all the time.
2. Doctor: Why don't patients make some effort to look after themselves? My surgery is full of people who eat, drink, smoke and don't get any exercise. Of course he may have many more patients who do look after themselves and don't often turn up in his surgery.
3. Why do young people all take drugs and go around mugging old ladies? You read about it in the paper all the time!
4. Child: When I grow up I want to be a singer. Have you seen how much money those pop-stars make?!