Unformatted text preview: E [ L ]. c. ±ind the covariance COV ( L, T ). d. ±ind the correlation coe²cient ρ L,T . 2. (2 pts) Consider the Following joint pdF f X,Y ( x, y ) = ( e2  yx 2 x∞ < y < ∞ , x ≥ else ±ind E [ Y  X = x ]. 3. (4 pts) The random variables Y 1 , Y 2 , Y 3 and Y 4 have the joint PD± f Y 1 ,Y 2 ,Y 3 ,Y 4 ( y 1 , y 2 , y 3 , y 4 ) = ( 4 ≤ y 1 ≤ y 2 ≤ 1 , ≤ y 3 ≤ y 4 ≤ 1 else a. ±ind the marginal pdF f Y 2 ,Y 3 ( y 2 , y 3 ). b. ±ind the marginal pdF f Y 3 ( y 3 ). 1...
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 Fall '08
 GELFAND
 Variance, Probability theory, probability density function, random variables Y1

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