Unformatted text preview: A P A P A A A P + + + = ∪ ∪ ∪ Theorem 3.5 If A is an event in the finite sample space S , then P( A ) equals the sum of the probabilities of the individual outcomes comprising A . Theorem 3.6 (Generalized addition rule) If A and B are any events in S , then ). ( ) ( ) ( ) ( B A P B P A P B A P ∩+ = ∪ Theorem 3.7 (Complement rule) If A is any event in S , then ). ( 1 ) ( A P A P c= EXAMPLE: The probability that an integrated circuit chip will have defective etching is 0.2, the probability that it will have a crack defect is 0.3, and the probability that it has both defects is 0.1. What is the probability that a newly manufactured chip will have either an etching or a crack defect? (See problem 3.46)...
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 Fall '03
 Mendell
 Probability, Probability theory, mutually exclusive events, Probability Equiprobable model

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