Interpretations of Probability
Updated 2026-09-10
INTRODUCTION
English translation pending.
CORE DEFINITION
Russell once quipped that probability is the most important concept in modern science, yet nobody can say clearly what it means. What a claim like a 30 percent chance of rain tomorrow asserts is a metaphysical question about what probability is and what makes such claims true. Competing interpretations, including frequency, subjective, propensity, and best-system accounts, each assign probability to a different kind of entity.
SCAFFOLDING EFFECT
Reduce cognitive load
- Value clarification: ask first whether the probability is assigned to a frequency, a propensity, or a degree of belief, then decide how to set its value. - Method selection: choose statistical tools according to the interpretation, rather than applying frequency conclusions to single events.
Anchor fast decisions
The probability calculus gives only formal constraints, non-negativity, normalization, and additivity, without fixing a semantics. Interpretations differ over what probability is assigned to: ratios of equally likely cases, logical relations among evidence, an agent's degree of belief, long-run frequencies, objective propensities of single trials, or patterns in best-system laws. Different objects make the same number mean different things.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- plato.stanford.eduhttps://plato.stanford.edu/entries/probability-interpret/verified
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