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Experiments and random variables can be grouped into families, where all random variables in family share a certain structure and particular random variable in a family is described by parameters.X = number of successes in n trials, X is a Binomial random variable with parameters (n,p)Permutations:Pk,n (number of combinations of size k from group of n objects) = n!(n-k)!order mattersCombinations:Ck,n = n!(n-k)! k!Order doesn’t matterPMF (probability mass function) – derivative of CDF (cumulative distributive function)CDF = sum of PMFsPoisson family of random variables – model for number of successes in experiment consisting of large number of independent trials with small probability of success for each trialEx: number of misprints in a bookBusiness Stat Lecture 3 01/26/2012Experiments and random variables can be grouped into families, where all random variables in family share a certain structure and particular random variable in a family is described by parameters.X = number of successes in n trials, X is a Binomial random variable with parameters (n,p)Permutations:-Pk,n (number of combinations of size k from group of n objects) = n! (n-k)!-order mattersCombinations:-Ck,n = n! (n-k)! k!-Order doesn’t matterPMF (probability mass function) – derivative of CDF (cumulative distributive function)CDF = sum of PMFsPoisson family of random variables – model for number of successes in experiment consisting of large number of independent trials with small probability of success for each trial-Ex: number of misprints in a

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