4a). Let X1 and X2 be independent random variables with a common cumulative distribution function...
Let X1, X2, ... be independent continuous random variables with a common distribution function F and density f. For k > 1, let Nk = min{n>k: Xn = kth largest of X1, ... , Xn} (a) Show Pr(Nx = n) = min-1),n>k. (b) Argue that fxx, (a) = f(x)+(a)k-( ++2)(F(x)* (c) Prove the following identity: al= (+*+ 2) (1 – a)', a € (0,1), # 22. i
3. Let {X1, X2, X3, X4} be independent, identically distributed random variables with p.d.f. f(0) = 2. o if 0<x< 1 else Find EY] where Y = min{X1, X2, X3, X4}.
Let Ņ, X1. X2, . . . random variables over a probability space It is assumed that N takes nonnegative inteqer values. Let Zmax [X1, -. .XN! and W-min\X1,... ,XN Find the distribution function of Z and W, if it suppose N, X1, X2, are independent random variables and X,, have the same distribution function, F, and a) N-1 is a geometric random variable with parameter p (P(N-k), (k 1,2,.)) b) V - 1 is a Poisson random variable with...
Consider two independent random variables X1 and X2. (continuous) uniformly distributed over (0,1). Let Y by the maximum of the two random variables with cumulative distribution function Fy(y). Find Fy (y) where y=0.9. Show all work solution = 0.81
Let Xi and X2 independent random variables, with distribution functions F1, and F2, respectively Let Y a Bernoulli random variable with parameter p. Suppose that Y, X1 and X2 are independent. Proof using the de finition of distribution function that the the distribution function of Z =Y Xit(1-Y)X2 is F = pF14(1-p)F2 Don't use generatinq moment functions, characteristic functions) Xi and X2 independent random variables, with distribution functions F1, and F2, respectively Let Y a Bernoulli random variable with parameter...
The random variables X1, X2, - .. are independent and identically distributed with common pdf 0 х > fx (x;0) (2) ; х<0. This distribution has many applications in engineering, and is known as the Rayleigh distribution. 2 (a) Show that if X has pdf given by (2), then Y = X2/0 is x2, i.e. T (1, 2) i.e. exponential with mean 2, with pdf fr (y;0) - ; y0; (b) Show that the maximum likelihood estimator of 0 is...
$ 200, if x > 10 else 3) Let X1, X2,..., X, bei.i.d. random variables from a population with f(x;0) = 0 > 0 being unknown parameter. a) Sketch a graph of a density from this family for a fixed 0. b) Find the cumulative distribution function F(x;0) of X1. c) Show that X (1) is a minimal sufficient statistic for e. 2n02n o d) Show that the density of X(1) is given by fx y2n +T, if y (y;0)...
Let X1, X2, ..., Xr be independent exponential random variables with parameter λ. a. Find the moment-generating function of Y = X1 + X2 + ... + Xr. b. What is the distribution of the random variable Y?
et Xi and X2 be independent random variables with common distribution NORM(8,1), where θ is a real number. Let Y = X1 + X a) Find the p.d.f. of Y. 4. L 2. b) Use the appropriate table to find P(Y> 20 + 2)
4 points) Let X1, X2 be independent random variables, with X1 uniform on (3,9) and X2 uniform on (3, 12). Find the joint density of Y = X/X2 and Z = Xi X2 on the support of Y, Z. f(y, z) =