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Unformatted text preview: Y ( y ) = 2e-2 y u( y ). 5. Let Y = e X . a. Find the cdf and pdf of Y in terms of the cdf and pdf of X. b. Find the pdf of Y when X is a Gaussian random variable. 6. Find the mean and variance of the binomial random variable. 7. Show that E[X] for the random variable with cdf & ± ² < ≥-= 1 1 / 1 1 ) ( x x x x F X does not exist. 8. Let Y = Acos( & t )+c, where A is a random variable with mean m and variance ± 2 , and & and c are constants. Find the mean and variance of Y. 9. Let g(X) = ba X , where a and b are positive constants and X is a Poisson random variable. Find E[g(X)]....
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- Fall '08
- Normal Distribution, Probability theory, Exponential distribution, CDF, Gaussian random variable