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These axioms are known as the Kolmogorov Axioms, after A. Kolmogorov who developed them. |
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These axioms are known as the Kolmogorov Axioms, after Andrey Kolmogorov who developed them. |
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Alternatively, a probability is a measure on a set of events, such that the measure of the whole set equals 1. |
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Alternatively, a probability is a measure on a set of events, such that the measure of the whole set equals 1. This property is important, since it gives rise to the natural concept of conditional probability. Every set A with non-zero probability defines another probability on the space: P(B|A) = P(B intersection A)/P(A). This is usually read as "probablity of B given A". B and A are said to be independent if the conditional probability of B given A is the same as the probability of B. |
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