3. Let Y ~N(μ, σ2), that is, e2g2 (y-H)2 2πσ2 Let ZY, Use the method of...
Let Zi, Z.Zg be a random sample of size 3 from the N(μ = 0, σ2-1) distribution. Let Xi, X2 be a random sample of size 2 from the N( 1-0,02-2) distribution. Let Y.Y2, Y be a random sample of size 3 from the N(11-1,ơ2-3) distribution. The Xi, Y, and Zi are all mutually independent. Give the distribution (including parameters) of each of the following: 2
8. Let Xi be iid N(μ, σ2) random variables. Define Y-Σ, Xi-Find the distribution of Y. a.
, X,' up N(μ, σ2), with σ2 known. Let μη-Xn + 5. Let Xi, of u be an estimator (a) Is ,hi an unbiased estimator for μ? (b) For a particular fixed n, find the distribution of (c) Find the mean squared error (MSE) of . (d) Prove that μη is consistent for μ
. Let Yi, ,Ý, be a sample from N(μ, σ2) distribution, where both μ and σ2 are un known Repeat the argument that was given in class to show that is a pivot (start by representing Yj as a linear function of a N(0, 1) random variable). Use the fact that (n-pe, of freedom") to construct the confidence interval with coverage probability 95% for σ2 (you can state the answer in terms of quantiles of X2-distribution, or find their numerical...
1. Let X1, X2, , Xn be independent Normal μ, σ2) random variables. Let y,-n Σ_lx, denote a sequence of random variables (a) Find E(y,) and Var(y,) for all n in terms of μ and σ2. (b) Find the PDF for Yn for alln. (c) Find the MGF for Yn for all n.
Problem 5 of 5Sum of random variables Let Mr(μ, σ2) denote the Gaussian (or normal) pdf with Inean ,, and variance σ2, namely, fx (x) = exp ( 2-2 . Let X and Y be two i.i.d. random variables distributed as Gaussian with mean 0 and variance 1. Show that Z-XY is again a Gaussian random variable but with mean 0 and variance 2. Show your full proof with integrals. 2. From above, can you derive what will be the...
σ2). 6. Suppose X1, Yİ, X2, Y2, , Xn, Y, are independent rv's with Xi and Y both N(μ, All parameters μί, 1-1, ,n, and σ2 are unknown. For example, Xi and Yi muay be repeated measurements on a laboratory specimen from the ith individual, with μί representing the amount of some antigen in the specimen; the measuring instrument is inaccurate, with normally distributed errors with constant variability. Let Z, X/V2. (a) Consider the estimate σ2- (b) Show that the...
8. Let X, X2, , xn all be be distributed Normal(μ, σ2). Let X1, X2, , xn be mu- tually independent. a) Find the distribution of U-Σǐ! Xi for positive integer m < n b) Find the distribution of Z2 where Z = M Hint: Can the solution from problem #2 be applied here for specific values of a and b?
4. Suppose Yi Y, are id randonn variables with E(Y )-μ, Var(Y)= σ2 < o For large n, find the approximaate distribution of YBeure to name any theorems you used.
Let Xi, ,Xn be a sample from N(μ, σ2) and assume that both parameters are unknown. Consider testing where μοισ., are given constants. Use LRT to derive the general form of the intersection-union rejection region in its simplest form. Identify the exact dis- tribution of statistics in the intersection-union rejection region . Hint: Use the fact that when the sample is from a Normal distribution, sample mean and sample variance are statistically independent. Let Xi, ,Xn be a sample from...