Suppose that X and Y are random variables with the joint density function 1+ x - 5 < x < -2,2 < y< 5 f(x, y) = 0, elsewhere. Determine P(Y>4 |X<-4).
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- Let Xand Y be two continuous random variables with joint probability density [3x function given by: f(x.y)%D 0sysxsl elsewhere with E(X) = ECX)- EC) - EC*)= ;and E(XY) = 10 3 E(Y*) = - and E(XY) =; %3D Then the value of the variance of 2X+Y is: O 3/80 O 91/320 43/320 7/20Show that if X and Y are independent Exp(a)-distributed random vari- ables, then X/Y E F(2,2).(b) Let X₁, X₂, X3 be uncorrelated random variables, having the same variance ². Consider the linear transformations Y₁ = X₁ + X₂, Y₂ = X₁ + X3 and Y3 = X₂ + X3 . Find the correlations of Yi, Y; for i #j. (5 marks)
- Let X1, X2,... , Xn be independent Exp(A) random variables. Let Y = X(1)min{X1, X2, ... , Xn}. Show that Y follows Exp(nA) dis- tribution. Hint: Find the pdf of YIf X is a continuous random variable find the CDF and density of the function y = x/3Let X be a (continuous) uniform random variable on the interval [0,1] and Y be an exponential random variable with parameter lambda. Let X and Y be independent. What is the PDF of Z = X + Y.
- Suppose Y1 and Y2 are random variables with joint pdf (6(1 — у2), 0, 0 < y1 < y2 fv, otherwise Y1 Let U1 and U2 = Y,. Use the transformation technique to show that U, follows a uniform Y2 distribution from 0 to 1.Suppose that X and Y are independent and uniformly distributed random variables. Range for X is (−1, 1) and for Y is (0, 1). Define a new random variable U = XY, then find the probability density function of this new random variable.Let X and Y be jointly continuous random variables with joint PDF cx +1, 2,y> 0, x+ y<1 0, fx,x (x, y) = otherwise. Then the constant c= And the probability that P(Y < 2X²) = ;: Here a = and b =