# Statistical Confusion

A statistical generalization is a statement which is usually true, but not always true. Very often these are expressed using the word “most”, as in “Most conservatives favour welfare cuts.” Sometimes the word “generally” is used, as in “Conservatives generally favor welfare cuts.” Or, sometimes, no specific word is used at all, as in: “Conservatives favour welfare cuts.”

Fallacies involving statistical generalizations occur because the generalization is not always true. Thus, when an author treats a statistical generalization as though it were always true, the author commits a fallacy.

- Accident
A generalization is applied when circumstances suggest there should be an exception.

- Converse Accident
An exception to a generalization is applied to cases where the generalization should apply.

Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statisticsby Gary SmithHow to Lie with Statisticsby Darrell HuffStatistics Done Wrong: The Woefully Complete Guideby Alex Reinhart