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)
Let X1,X2 be two independent exponential random variables with λ=1, compute the P(X1+X2<t) using the joint...
2. Let Xi exp(1) and X2 ~ variables with rate 1. Let: erp(1) be independent and identically-distributed exponential random (a) What is the cdf of X1? b) What is the joint pdf of (Xi, X2)? (c) What is the joint pdf of (Y, Z)? d) What is the marginal pdf of z?
Let X1 + X2 +...+ X30 be independent and identically distributed exponential random variables with mean 1. Calculate the probability that X ¯ is greater than 1.1. a. 29% b. 71% c. 35%
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.
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?
Let X1, X2, X3 ∼(iid) Exponential(λ). (a) Show that T(X1, X2, X3) = X1 + X2 + X3 is a sufficient statistic for λ. (b) Find the MVUE for λ. (c) Show that is not a sufficient statistic for λ. (d) Let = and find . Give an argument for why is not the best estimator of λ. We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to...
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) .
14. Let X1, X2, X3 be independent random variables that represent lifetimes (in hours) of three key components of a device. Suppose their respective distributions are exponential with means 1000, 1500, and 2000. Let Y be the minimum of Xi, X2, X3 and compute P(Y 1000).
Exercise 6.48. Let X1, X2, ..., Xin be independent exponential random variables, with parameter lį for Xi. Let Y be the minimum of these random variables. Show that Y ~ Exp(11 +...+ In).
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...
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}.