IPHY 2500 Lecture Notes - Lecture 10: Bayes Estimator, Dependent And Independent Variables
3 Oct 2016
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Definition: the conditional probability of event b, given event a, is p(b | a) = p(a and: / p(a, note that when we evaluate the conditional probability, we always divide by the probability of the given event. The probability of both goes in the numerator: the above formula holds as long as p(a) > 0, since we cannot divide by 0. The event whose probability we is written first, the vertical line stands for the word. P(b | a) differ: if p(b | a) = p(b | not a) they are independent another method for checking the independence of events a and b is to compare p(a and, to p(a) * p(b). If the two are equal, then a and b are independent, otherwise the two are not independent. General multiplication rule a formal rule for finding p(a and b) that applies to any two events, whether they are independent or dependent.
