X denote the mean of a random sample of size 25 from a gamma type distribu-...
Just need to solve Problem 4 4.2.14. Let X denote the mean of a random sample of size 25 from a gamma-type distribution with a = 4 and 3 > 0. Use the Central Limit Theorem to find an approximate 0.954 confidence interval for pl, the mean of the gamma distribution. Hint: Use the random variable (X - 43)/(432/25)/2 = 5X/23 - 10. 21 TL11C1L We were unable to transcribe this image
Suppose Y1, ..., Yn denote a random sample of size n from an exponential distribu- tion with mean 0. a) (5 points) Find the bias and MSE of the estimator ôz = nY1). b) (3 points) Consider another estimator ôz = Y. Find the efficiency of ôı relative to 62. c) (7 points) Prove that 297 Yi is a pivotal quantity and find a 95% confidence interval for 0.
Leth < ½ < Y, denote the order statistics of a random sample of size 3 from a distribution with pdff(x) = 1,0 x < 1 zero elsewhere. Let Z Ling e the midrange of the sample an d R = Y 3-Y, be the range ofthe sample. (a) Find the joint pdf of (Z, R). (b) Find the probability that the range is less than 0.5 (c) Find the pdf of Z.
4. Let Yi, . .. ,y, denote a random sample from the pdf 0-1 0Ky1, elsewhere. y"(1- y)0-1 0, (a) Find the method of moments estimator of θ. (b) Find a sufficient statistics for θ 4. Let Yi, . .. ,y, denote a random sample from the pdf 0-1 0Ky1, elsewhere. y"(1- y)0-1 0, (a) Find the method of moments estimator of θ. (b) Find a sufficient statistics for θ
3.4 Let X,, X be a random sample of size n from the U(Q,62) distribution, 6, and let Y, and Yn be the smallest and the largest order statistics of the Xs (i) Use formulas (28) and (29) in Chapter 6 to obtain the p.d.f.'s of Y and Y and then, by calculating depending only on Yi and 1,- Part i. (Note: it is not saying to find the joint pdf of Yi and Yn Find their marginal Theorem 13...
6. Let X1, . . . , Xn denote a random sample (iid.) of size n from some distribution with unknown μ and σ2-25. Also let X-(1/ . (a) If the sample size n 64, compute the approximate probability that the sample mean X n) Σηι Xi denote the sample mean will be within 0.5 units of the unknown p. (b) If the sample size n must be chosen such that the probability is at least 0.95 that the sample...
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.
Let X1, X2, ..., X48 denote a random sample of size n = 48 from the uniform distribution U(?1,1) with pdf f(x) = 1/2, ?1 < x < 1. E(X) = 0, Var(X) = 1/3 Let Y = (Summation)48, i=1 Xi and X= 1/48 (Summation)48, i=1 Xi. Use the Central Limit Theorem to approximate the following probability. 1. P(1.2<Y<4) 2. P(X< 1/12)
Problem 5 Let Y1 denote the minimum of a random sample of size n from a distribution that has pdf f(x) e(,0x< o0, zero elsewhere X- n (Y1 0), find the cumulative distribution function (cdf) for Zn = n (Y1 - 0), and Let Zn find the limiting cdf of Zn as n >oo.
Show that the mean X bar of a random sample of size n from a distribution having probability density function f(x;θ)=(1/θ)e-(x/θ) , ,0 < x < ∞ , 0 < θ < ∞ , zero elsewhere, is an unbiased estimator of θ and has variance θ2/n.