otherwise statistics r e x p 2 varx math

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Unformatted text preview: r , r + 1, r + 2, . . . otherwise Statistics: r µ = E (X ) = p σ 2 = Var(X ) = Math 30530 (Fall 2012) rq p2 Discrete Random Variables October 7, 2012 5 / 10 The Discrete Uniform random variable Name: D.Uniform(N ) When to use: When you are assigning values 1 through N to N equally likely outcomes Parameter: N : the number of outcomes Mass function: pX (x ) = 1 N 0 if x = 1, 2, 3, . . . , N otherwise Statistics: µ = E (X ) = N + 1 2 2 − σ 2 = Var(X ) = N 12 1 Math 30530 (Fall 2012) Discrete Random Variables October 7, 2012 6 / 10 The Hypergeometric random variable Name: Hypergeometric(M , N , n) When to use: When you are selecting a fixed number of items from a fixed size pool, containing a fixed number of desirable objects, without replacement and with order not mattering, and you are counting how many of the selected objects are desirable Parameters: M : the number of desirable objects in the pool N : the total number of objects in the pool n: the number you are selecting (...
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This document was uploaded on 03/13/2014 for the course ECON 205 at American University of Beirut.

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