Lecture15_Chapter3

# Lecture15_Chapter3 - Lecture 15 Chapter 3 Wednesday October...

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Lecture 15 – Chapter 3 Wednesday, October 15 th

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Hypergeometric Experiment ± A hypergeometric experiment is one that satisfies: ² There is a population of N elements ² Each element can be characterized as a success or a failure ² We select a sample of n elements without replacement
Hypergeometric random variable ± In a hypergeometric experiment the random variable X = “number of successes in the sample” is called hypergeometric random variable ± Example: ² In a large box there are 20 white and 15 black balls. I randomly select 5 balls. Let X=# of white balls in the sample. Then X is a hypergeometric random variable

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Hypergeometric Distribution ± The Hypergeometric Distribution depends on three parameters: ² The sample size n ² The population size N ² The number of successes M in the population
Hypergeometric Distribution ± If X~Hypergeometric(N, M, n) then: ± where () M NM xn x PX x N n ⎛⎞ ⎜⎟ ⎝⎠ == ( ) ( ) max 0, min , nN M x n M −+

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Mean, Variance ±
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• Fall '08
• staff
• Probability, Probability theory, Binomial distribution, Discrete probability distribution, Negative binomial distribution, Hypergeometric Distribution, negative binomial experiment

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Lecture15_Chapter3 - Lecture 15 Chapter 3 Wednesday October...

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