lec20 - UCI University of California, Irvine EECS 161 -...

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EECS 161 - Introduction to Computer Networking Scott Jordan Performance UCI University of California, Irvine Discrete Random Variables set of outcomes = . associated probabilities = , i.e. . "X" is a Random Variable (R.V.) must hold. x 1 x 2 x n ,, , {} p 1 p 2 p n ,,, { } PX x i = () p i = x 1 x 2 x 3 p 1 p 3 p 2 p i i 1 =
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EECS 161 - Introduction to Computer Networking Scott Jordan Performance UCI University of California, Irvine Discrete Random Variables Example: "Poisson R.V." set of outcomes = . where is a constant > 0. 012 ,,, {} PX n = () e α α n n ! ------ = α 34567 n =
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EECS 161 - Introduction to Computer Networking Scott Jordan Performance UCI University of California, Irvine Continuous Random Variables set of outcomes = . associated relative probabilities "density function", i.e. , or must hold. ∞∞ , () f x PX xx dx + , fx dx = f x lim Δ x 0 xx Δ x + , Δ x --------------------------------------------- = f(x) x x d 1 =
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EECS 161 - Introduction to Computer Networking Scott Jordan Performance UCI University of California, Irvine Continuous Random Variables Example: "Exponential R.V." set of outcomes = .
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This note was uploaded on 03/28/2009 for the course CSE 120A taught by Professor Healey during the Spring '08 term at UC Irvine.

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lec20 - UCI University of California, Irvine EECS 161 -...

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