need solution 1. [5 marks] The proportion of lost packets Types I and II in a network are random variables X1 and X2...
Let X1 and X2 be two discrete random variables, where X1 can attain values 1, 2, and 3, and X2 can attain values 2, 3 and 4. The joint probability mass function of these two random variables are given in the table below: X2 X1 2 3 4 1 0.05 0.04 0.06 2 0.1 0.15 0.2 3 0.2 0.1 0.1 a. Find the marginal probability mass functions fX1 (s) and fX2 (t). b. What is the expected values of X1...
Let (X1, Y1) and (X2, Y2) be independent and identically distributed continuous bivariate random variables with joint probability density function: fX,Y (x,y) = e-y, 0 <x<y< ; =0 , elsewhere. Evaluate P( X2>X1, Y2>Y1) + P (X2 <X1, Y2<Y1) .
two random variables x1 and x2 have a joint probability density function f(x1,x2)={x1+x2, 0<x1<1, 0<x2<1 0, otherwise what is the marginal distribution of x1 and x2
12. Suppose that X1, X2, ,X40 denote a random sample of measurements on the proportion of impurities in iron ore samples.Let each variable X, have a probability density function given by 3x2 0<1 elsewhere fx(x)= The ore is to be rejected by the potential buyer if sample of size 40. X, exceeds 2.8. Estimate P( X,> 2.8) for the
Let X- (Xi, X2,X3) be an absolutely continuous random vector with the joint probability density function elsewhere. Calculate 1. the probability of the event A -(Xs 3. the probability density function xx (,s) of the (XX)-marginal 4. the probability density function fx, () of the Xi-marginal, and the probability density function fx (r3) of the X3-marginal 5. Are Xi and X independent random variables? 6. E(Xi) and Var(X) 8. the covariance cov(Xi, X3) of Xi and X,3 9. Which elements...
Let X1 and X2 be independent exponential random variables with parameters λ1 and λ2respectively. Find the joint probability density function of X1 + X2 and X1 − X2.
I need the solution of this question asap 3, Cov(X1, X2) = 2, Cov(X2, X3) = -2, 5. Let Var(x1) = Var(X3) = 2, Var(X2) Cov(X1, X3) = -1. i) Suppose Y1 = X1 - X2. Find Var(Y1). ii) Suppose Y2 = X1 – 2X2 – X3. Find Var(Y2) and Cov(Y1, Y2). Assuming that (X1, X2, X3) are multivariate normal, with mean 0 and covariances as specified above, find the joint density function fyy, y,(91, y2). iii) Suppose Y3 =...
1. Let X1, X2, X3 be continuous random variables with joint probability density function 00 < Xi < 00,i=1,2,3 Consider the transformation U-X1, V = X , W-XY + X + X (a) Find the joint pdf (probability density function) of U, V and W. (b) Find the marginal pdf of U, and hence find E(U) and Var(U) (c) Find the marginal pdf of W, and hence find E(W) and Var(W) (d) Find the conditional pdf of U given Ww,...
Let X1,X2 be two independent exponential random variables with λ=1, compute the P(X1+X2<t) using the joint density function. And let Z be gamma random variable with parameters (2,1). Compute the probability that P(Z < t). And what you can find by comparing P(X1+X2<t) and P(Z < t)? And compare P(X1+X2+X3<t) Xi iid (independent and identically distributed) ~Exp(1) and P(Z < t) Z~Gamma(3,1) (You don’t have to compute) (Hint: You can use the fact that Γ(2)=1, Γ(3)=2) Problem 2[10 points] Let...
20 marksConsider the multinomial distribution with 3 categories, where the random variables X1,X2 and X have the joint probability function 123 [4 marks] Find the approximate distribution of Y = 2X1-X2, when the sample size n is large. 20 marksConsider the multinomial distribution with 3 categories, where the random variables X1,X2 and X have the joint probability function 123 [4 marks] Find the approximate distribution of Y = 2X1-X2, when the sample size n is large.