Statistical Sciences 2141A/B Lecture Notes - Lecture 18: Gamma Distribution, Poisson Point Process, Reliability Engineering

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The most important properties of the gamma function are: For any positive integer, n, (cid:894)n(cid:895) = (cid:894)n 1)! For a(cid:374)(cid:455) k > (cid:1005), (cid:894)k(cid:895) = (cid:894)k 1) (k - 1) via integration by parts. It has a state space x 0. The para(cid:373)eters of the distri(cid:271)utio(cid:374) are k > (cid:1004) a(cid:374)d > (cid:1004) A gamma random variable x is an rv that is used in areas such as reliability theory and the analysis of a poisson process. The exponential is just a particular case of the gamma where k =1. This i(cid:373)plies that for a poisso(cid:374) pro(cid:272)ess (cid:449)ith para(cid:373)eter , the ti(cid:373)e take(cid:374) for k e(cid:448)e(cid:374)ts to o(cid:272)(cid:272)ur has a gamma distribution. Suppose the survival time x in weeks of randomly selected male mouse exposed to 240 rads of gamma radiation has a gamma distribution with k =8 a(cid:374)d = (cid:1005)/(cid:1005)5.

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