This came up in a discussion a few years ago, where people were arguing about the meaning of probability: is it long-run frequency, is it subjective belief, is it betting odds, etc? I wrote:

Probability is a mathematical concept. I think Martha Smith’s analogy to points, lines, and arithmetic is a good one. Probabilities are probabilities to the extent that they follow the Kolmogorov axioms. (Let me set aside quantum probability for the moment.) The different definitions of probabilities (betting, long-run frequency, etc), can be usefully thought of as models rather than definitions. They are different examples of paradigmatic real-world scenarios in which the Kolmogorov axioms (thus, probability).

Probability is a mathematical concept. To define it based on any imperfect real-world counterpart (such as betting or long-run frequency) makes about as much sense as defining a line in Euclidean space as the edge of a perfectly straight piece of metal, or as the space occupied by a very thin thread that is pulled taut. Ultimately, a line is a line, and probabilities are mathematical objects that follow Kolmogorovâ€™s laws. Real-world models are important for the application of probability, and it makes a lot of sense to me that such an important concept has many different real-world analogies, none of which are perfect.

We discuss some of these different models in chapter 1 of BDA.

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