Suppose X1, X2, ..., Xn are independent and identically distributed (iid) with a Uniform -0,0 distri-...
Let X1,... , Xn be independent random variables, each following an exponential distri- bution with rate λ. Let Y = min(X1, .. . , Xn). Find the cd.f. and pdf. of Y. HINT:
1. Let X1, X2,... , Xn be independent and identically distributed according to the unifornm distribution on (0,1). Let Xn and fn denote the 6th smallest and its pdf, respectively Determine fn(x) limn
Question 1: Suppose that X1, X2,... Xn are independent identically distributed continuous outcome random variables which have a probability density function (pdf) f(z) = π1+ア Calculate (with all working) the pdf of the average of the X,i Comment on the significance of this result to sampling from a random vari- able with the pdf f. This pdf is called a Cauchy density.
Consider n independent and identically distributed random variables X1,X2, following a uniform distribution on the interval [0,1] ,Xn, each a) What is the pdf of Mmin(X1,X2, .. ,Xn)? b) Give the expectation and variance of XX 1-1лі.
1. The random variables Xi, X2,... are independent and identically distributed (iid), . .. are independent and identica each with pdf f given in Assignment 4, Question 1. Let s, X1 + . .. + Xn. Using the Central Limit Theorem and the graph of the standard normal distribution in Figure 1, approximate the probability P(S100 > 600). Express your answer in the format x.x - 10*. Verify your answer by simulating 10,000 outcomes of S1o0 and counting how many...
Again, let X1,..., Xn be iid observations from the Uniform(0,0) distribution. (a) Find the joint pdf of Xi) and X(n)- (b) Define R = X(n)-X(1) as the sample range. Find the pdf of R. (c) It turns out, if Xi, . . . , xn (iid) Uniform(0,0), E(R)-θ . What happens to E® as n increases? Briefly explain in words why this makes sense intuitively.
2. (15pts) Let X1, X2 be independent and identically distributed with Uniform(0,) density. (a) Is Y-X1 + X2 a sufficient statistic for θ? Hint: You need to find the conditional density of (X1, X2) given Y = X1 + X2. (b) Consider now S := max(X1, X2). 1s S a sufficient statistics for θ?
Suppose that X1, X2, .., Xn are iid Poisson observations, each having common pdf 0 e-8 0, otherwise. Find the UMVUE of τ(0)-g2.
2. Let X1, X2,. . , Xn denote independent and identically distributed random variables with variance σ2, which of the following is sufficient to conclude that the estimator T f(Xi, , Xn) of a parameter 6 is consistent (fully justify your answer): (a) Var(T) (b) E(T) (n-1) and Var(T) (c) E(T) 6. (d) E(T) θ and Var(T)-g2. 72 121
(a) Suppose that X1, X2,... are independent and identically distributed random variables each taking the value 1 with probability p and the value -1 with probability 1-p. For n = Yn-X1 + X2 + . . . + Xn. Is {Y, a Markov chain? If so, write down its state space and transition probability matrix 1, 2, . . ., denne