Hasty Generalization and Cherry-Picking

Recognize conclusions drawn from too few examples or from carefully selected ones.

A hasty generalization draws a broad conclusion from too small or unrepresentative a sample. 'I met two rude people from that town, so people there are rude. ' Two people cannot represent a whole population. Cherry-picking is a related problem: selecting only the evidence that supports a claim while ignoring evidence against it. Worked example: an article argues that a city's crime rate is soaring, citing three dramatic incidents from the past month.

If city records show overall crime fell 8 percent that year, the article has cherry-picked vivid cases and generalized hastily from them. Vivid stories are powerful because they are memorable, but memorability is not frequency. To evaluate a generalization, ask: how many cases support it? How were they chosen? What does the full data say? Strong generalizations rest on large, representative samples and acknowledge counterexamples rather than hiding them.

• 1Hasty generalizations rely on too few or unrepresentative cases.
• 2Cherry-picking selects only supporting evidence.
• 3Ask how many cases, how chosen, and what the full data says.