Cov(X,Y) = E(XY) - E(X).E(Y)
= 9 - 8 = 1
Var(X) = E(X2) - (E(X))2
= 6 - 4 = 2
Var(Y) = E(Y2) - (E(Y))2
= 18 - 16 = 2
Correlation of X and Y is XY = Cov(X,Y) /
(V(X).V(Y) )1/2
= 1/2
Note : while doing integration we excluded f(X,Y) for x =y, as integration is 0 for measure 0 set
8), Let X and Y be continuous random variables with joint density function f(x,y)-4xy for 0 < x < y < 1 Otherwise What is the joint density of U and V Y
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1. Let X and Y be random variables with joint probability density function flora)-S 1 (2 - xy) for 0 < x < 1, and 0 <y <1 elsewhere Find the conditional probability P(x > ]\Y < ).
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Let X and Y be random variables with joint density function f(x,y) бу 0 0 < y < x < 1 otherwise The marginal density of Y is fy(y) = 3y (1 – y), for 0 < y < 1. True False