Téori probabilitas: Béda antarrépisi

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The probability that an event <math>E</math> occurs ''given'' the known occurrence of an event <math>F</math> is the '''[[conditional probability]]''' of <math>E</math> '''given''' <math>F</math>; its numerical value is <math>P(E \cap F)/P(F)</math> (as long as <math>P(F)</math> is nonzero). If the conditional probability of <math>E</math> given <math>F</math> is the same as the ("unconditional") probability of <math>E</math>, then <math>E</math> and <math>F</math> are said to be [[statistical independence|independent]] events. That this relation between <math>E</math> and <math>F</math> is symmetric may be seen more readily by realizing that it is the same as saying
<math>P(E \cap F) = P(E)P(F)</math>. turkey
Two crucial concepts in the theory of probability are those of a [[variabel acak]] and of the [[probability distribution]] of a random variable; see those articles for more information.