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Unformatted text preview: Week 9 F Distribution Inequalities Convergence F distribution and F statistic Chebyshevs Inequality Let k > 0 and let Y be a rv with mean and variance 2 . Then 2 1 (  ) P Y k k and 2 1 (  ) 1 P Y k k Proof : 2 2 2 2 ( ) {( ) (  )} {( ) (  )} E Y E Y I Y k E Y I Y k 2 {0 (  )} {( ) (  )} E I Y k E k I Y k 2 2 (  ) k P Y k . Applications: Used to prove many probabilistic results including the weak law of large numbers. Markovs Inequality For any rv U and real numbers x , p > 0, (  )   p p P U x x E U . Bivariate Normal The multivariate normal distribution Suppose that the pdf of 1 ( ,..., ) k Y Y Y is given by 1 / 2 1/ 2 1 1 ( ) exp ( ) ( ) (2 )   2 n f y y y...
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 Three '08
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 Law Of Large Numbers, Variance

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