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Unformatted text preview: μ = 1 2 3 and variance matrix M = 1 0 1 0 2 1 1 1 3 (a) Calculate E ( X 1 + 2 X 2 + 3 X 3 ). (b) Calculate var( X 1 + 2 X 2 + 3 X 3 ). 3 4. [20 pts.] Suppose a basketball player is shooting free throws and the results (success or failure) are considered to be independent and identically distributed Bernoulli random variables with success probability 3 / 4 (code success as one and failure as zero). The player shoots three free throws. What is the probability that she makes at least one? 5. [20 pts.] Suppose the random vector ( X,Y ) has PMF given by f ( x,y ) = x 2 y 90 , x =2 ,1 , , 1 , 2 , y = 2 , 3 , 4 . Are X and Y independent random variables? Explain why or why not, as the case may be. 4...
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This note was uploaded on 10/28/2010 for the course STAT 5101 taught by Professor Staff during the Spring '02 term at Minnesota.
 Spring '02
 Staff

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