Suppose X1, X2, . . . are independent discrete random variables, having the same distribution, and E[Xi] > 0, for each i. Is thus true for any two positive integers n and m?:
Why not, or why yes?
Suppose X1, X2, . . . are independent discrete random variables, having the same distribution, and...
Suppose the random variables X1, X2, ..., Xn are independent each with the distribution 020 *; 0) (0+1); X2 2. Find the Maximum Likelihood estimate for 0. On Žin(x) + • 8Žin(x) + n In(2) i= 1 { ince) -- OD. Žince) - n ince) -n In(2) i= 1 O e. None of the above.
L.11) Sums of independent random variables a) If X1 , X2 X, , , Xn are independent random variables all with Exponential μ distribution, then what is the distribution of XII + 2 +X3 + .tX b) If X is a random variable with Exponential[u] distribution, then what is the distribution of x +X1? c) If X1 , X2 , Х, , , X are independent random variables all with Normal 0. I distribution, then what is the distribution of...
a) If X1 and X2 are independent random variables and X1 tollows the Nor nalLA σ1 X, +X2 follow? di tri t on and X to ows the Nonna μα 2 distribution, ne ha distribution do b) IfX1 , X2 . X, , arendependent random variables and each Xk follows the NormalA 에 ds rbutio. then what distribution does follow? , n L.6) Generating functions for sums of independent random variables a) If X and X are independent random variables,...
thanks Suppose that Xi and X2 are independent random variables each having PDF: : otherwise (a) Use the transformation technique to find the joint PDF of Yi and Ya where Y-X1 and ½ = Xi +X2. (b) Using your answer to part (a), and the fact that o Vu(1-u) find and identify the distribution of Y2.
3. Suppose that X1, X2, , Xn are independent random variables with the same expectation μ and the same variance σ2. Let X--ΣΑι Xi. Find the expectation and variance of
Properties of Expectation and Variance Suppose we have two independent discrete random variables, say X1 and X2. Suppose further E(X1) = 21 Var(X1) = 126 and E(X2) = 3.36 Var(X2) = 1.38 Compute the Expectations and Variances of the following linear combinations of X1 and X2. a) E(πX1 + eX2 + 17) b) E(X1 · 3X2) c) Var( (√ 13X2) + 46) d) Var(X1 + 2X2 + 14)
Let X1 and X2 be random variables, not necessarily independent. Show that E [X1 + X2] = E [X1] + E [X2]. You may assume that X1 and X2 are discrete with a joint probability mass function for this problem, while the above inequality is true also for continuous random variables.
1. Let X1, X2,... be independent random variables each with the standard normal distribution, and for each n 0 let Sn 너 1 i. Use importance sampling to obtain good estimates for each of the following probabilities: (a) P[maxns 100 Sn > 10); and (b) P[maxns100 Sn > 30 HINTS: The basic identity of importance sampling implies that n100 where Po is the probability measure under which the random variables Xi, X2,... are independent normals with mean 0 amd variance...
3. (25 pts.) Let X1, X2, X3 be independent random variables such that Xi~ Poisson (A), i 1,2,3. Let N = X1 + X2+X3. (a) What is the distribution of N? (b) Find the conditional distribution of (X1, X2, X3) | N. (c) Now let N, X1, X2, X3, be random variables such that N~ Poisson(A), (X1, X2, X3) | N Trinomial(N; pi,p2.ps) where pi+p2+p3 = 1. Find the unconditional distribution of (X1, X2, X3). 3. (25 pts.) Let X1,...
2. The random variables X1, X2 and X3 are independent, with Xi N(0,1), X2 N(1,4) and X3 ~ N(-1.2). Consider the random column vector X-Xi, X2,X3]T. (a) Write X in the form where Z is a vector of iid standard normal random variables, μ is a 3x vector, and B is a 3 × 3 matrix. (b) What is the covariance matrix of X? (c) Determine the expectation of Yi = Xi + X3. (d) Determine the distribution of Y2...