From 6.3-6. For n E N, let W < W<< W2nt be the order statistics of...
From 6.3-3. Let Yi < Y2 < < Yg be the order statistics of 9 independent draws from an exponential distribution that has a mean of 2. (1) Find the PDF of Y2 (2) Compute PIY9 < 1
From 6.3-3. Let Y1 < Y2 < . . . < Y9 be the order
statistics of 9 independent draws from an exponential distribution
that has a mean of 2.
(1) Find the PDF of Y2.
(2) Compute P[Y9 < 1].
From 6.3-3. Let Yǐ < ½ < . . . < y) be the order statistis of 9 independent draws from an exponential distribution that has a mean of 2. (1) Find the PDF of Y2 2) Compute PY,1
fx (z)='0 otherwise Let Xa)<...<Xn) be the order statistics. Show that Xa)/X(n) and X(n) are independent random variables.
4. Let X1,..., X, be a random sample from a population with pdf 0 otherwise Let Xo) <...Xn)be the order statistics. Show that Xu/Xu) and X(n) are independent random variables
For , let be the order statistics of independent draws from . (1) Find the PDF of . (2) Compute . We were unable to transcribe this imageWe were unable to transcribe this image(2n+1 Unif -1,1 We were unable to transcribe this imageWe were unable to transcribe this image
4. I. Let Yǐ < ½ < ⅓ < Ya be the order statistics of a random sample of size n = 4 from a distribution with pdf f(x) 322, 0<< 1, zero elsewhere. (a) Find the joint pdf of Ys and Ya (b) Find the conditional pdf of Ys, given Y-y (c) Evaluate Evsl (d) Compute the probability that the smallest of the random sample exceeds the median of the distribution
Let X1, ..., Xn be a random sample from a population with pdf f(x 1/8,0 < x < θ, zero elsewhere. Let Yi < < Y, be the order statistics. Show that Y/Yn and Yn are independent random variables
2. Let X be a continuous random variable with pdf f(x) = { cr", [w] <1, f() = 0. Otherwise, where the parameter c is constant (with respect to x). (a) Find the constant c. (b) Compute the cumulative distribution function F(2) of X. (c) Use F(2) (from b) to determine P(X > 1/2). (d) Find E(X) and V(X).
Let (In), and (yn).m-1 be sequences such that Pr – yn| < 1/n for all n. Use the definition of convergence to prove that, if (2n)_1 is convergent, then (Yn)-1 is convergent.
6. Let X1, X2,.. , Xn denote a random sample of size n> 1 from a distribution with pdf f(x; 6) = 6e-8, 0<x< 20, zero elsewhere, and 0 > 0. Le Y = x. (a) Show that Y is a sufficient and complete statistics for . (b) Prove that (n-1)/Y is an unbiased estimator of 0.