Hasty generalization

Hasty generalization is an informal fallacy of generalisation by making decisions based on too little evidence or without recognizing all of the variables. In statistics, it may mean basing broad conclusions of a survey from a small sample group.^[1]

A hasty generalization made from a single example is sometimes called the "fallacy of the lonely fact"^[2] or the "proof by example fallacy".^[3]

When evidence is intentionally excluded to bias the result, it is sometimes termed the "fallacy of exclusion".^[4]

Example

Hasty generalization may follow this pattern

X is true for A.

X is true for B.

X is true for C.

X is true for D.

Therefore, X is true for E, F, G, etc.