P(BIA)=P(A and B)/P(A) Probability of B given A P(BIA) does not = P(AIB) if it does, they’re dependent = ! - ! nPr n n r Use if ABC is different than CBA = ! - ! ! nCr n n r r Use if ABC is the same as CBA 0!=1 Probability Distribution Rules-1.) sum of all probabilities=1 2.) each value is between 0 and 1 inclusive µ=∑ x∙Px mean σ²=∑ [( - ) ( )] x µ ²∙P x variance σ²=∑ [ ( )]-x²∙P x µ² variance σ=∑ [ ( )]-x²∙P x µ² standard deviation Binomial Probability Rules-1.) procedure has a fixed number of trials, 2.) trials must be independent, 3.) results must be classified into 2 categories-success/failure, 4.) probability of success remains the same for all trials µ=np p =probability of success x =denotes specific #of successes in n trials (between 0 and n ) σ²=npq q =probability of failure p =probability of success in one of the n trials σ= npq n =number of trials q =probability of failure in one of the n trials = ! - ! !* *-Px n n x x px qn x
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This note was uploaded on 04/17/2008 for the course MATH unknown taught by Professor Sapko during the Fall '08 term at Mass Colleges.