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A statistical syllogism is an inductive syllogism. Statistical syllogisms may use qualifying words like "most", "frequently", "almost never", "rarely", etc., or may have a statistical generalization as one or both of their premises.

For example:

  1. Almost all people are taller than 26 inches
  2. Bob is a person
  3. Bob is taller than 26 inches

Premise 1 (the major premise) is a generalization, and the argument attempts to draw a conclusion from that generalization.

General form:

  1. X proportion of F are G
  2. I is an F
  3. I is a G

In the abstract form above, F is called the "reference class" and G is the "attribute class" and I is the individual object. So, in the earlier example, "(things that are) taller than 26 inches" is the attribute class and "people" is the reference class.

Unlike many other forms of syllogism, a statistical syllogism is inductive, so when evaluating this kind of argument we should be careful to stress how strong or weak it is, along with all the other rules of induction (as opposed to deduction).

Two dicto simpliciter fallacies can occur in statistical syllogisms. They are "accident" and "converse accident". Faulty generalization fallacies can also affect any argument premise that uses a generalization.

See also

he:סילוגיזם סטטיסטי

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