TOPIC: Use of chi-square distribution to find the required probability based on the sample variance.
Problem 4 (20 points). Show how to use the chi-square distribution to calculate P(a < S2...
DISTRIBUTION OF SAMPLE VARIANCE: Xn ~ N(μ, σ2), where both μ and σ are Problem 4 (25 points). Assume that Xi unknowin 1. Using the exact distribution of the sample variance (Topic 1), find the form of a (1-0) confidence interval for σ2 in terms of quantiles of a chi-square distribution. Note that this interval should not be symmetric about a point estimate of σ2. [10 points] 2. Use the above result to derive a rejection region for a level-o...
Problem 2 (20 points Assume X, . , Ņ(μ, σ2). Show that S-n-ι Σί=i( An is a random sample from the normal distribution Xi _ Λ )-Is an unbiased estimator of σ 2.
Problem 2 [17 points]. Transformations! a) (5 points) Suppose the time, W, it takes to complete a technical task at a workshop has probability density function -w/2 f(w)y 0, 0, otherwise Using the appropriate transformation methods, find the density function for the a time it takes two workers to complete this technical task: S Wi + Ws b) (5 points) Derive the moment generating function of a standard normal randon variable. Use point form to explain each step in your...
please answer with full soultion. with explantion. (4 points) Let Xi, , Xn denote a randon sample from a Normal N(μ, 1) distribution, with 11 as the unknown parameter. Let X denote the sample mean. (Note that the mean and the variance of a normal N(μ, σ2) distribution is μ and σ2, respectively.) Is X2 an unbiased estimator for 112? Explain your answer. (Hint: Recall the fornula E(X2) (E(X)Var(X) and apply this formula for X - be careful on the...
Let P be a distribution on R with variance σ2. Let X1, and let S2 be the associated unbiased estimator of σ2. 1, ,Xn be a random sample form P n-1 i-1 Show that 4 2ơ 2 Wa Feel free to "Cheat" and use the fact that (n - 1)s2 2 n-1 (Can you do it without "Cheating"?)
4. Let X1,X2, ,Xn be a randonn sample from N(μ, σ2) distribution, and let s* Ση! (Xi-X)2 and S2-n-T Ση#1 (Xi-X)2 be the estimators of σ2 (i) Show that the MSE of s is smaller than the MSE of S2 (ii) Find E [VS2] and suggest an unbiased estimator of σ.
1. (40) Suppose that X1, X2, Xn forms an independent and identically distributed sample from a normal distribution with mean μ and variance σ2, both unknown: 2nơ2 (a) Derive the sample variance, S2, for this random sample. (b) Derive the maximum likelihood estimator (MLE) of μ and σ2 denoted μ and σ2, respectively. (c) Find the MLE of μ3 (d) Derive the method of moment estimator of μ and σ2, denoted μΜΟΜΕ and σ2MOME, respectively (e) Show that μ and...
Let X1,X2, , Xn be a random sample from a normal distribution with a known mean μ (xi-A)2 and variance σ unknown. Let ơ-- Show that a (1-α) 100% confidence interval for σ2 is (nơ2/X2/2,n, nơ2A-a/2,n). Let X1,X2, , Xn be a random sample from a normal distribution with a known mean μ (xi-A)2 and variance σ unknown. Let ơ-- Show that a (1-α) 100% confidence interval for σ2 is (nơ2/X2/2,n, nơ2A-a/2,n).
4. Let Xi, , xn be a sample from N(μ, σ2). Use the distributions of sarnple mean X and sample variance s2 and Basu's theorem to show that sample mean and sample variance are independent.
4. Let X1,X2, x 2) distribution, and let sr_ Ση:1 (Xi-X)2 and S2 n-l Σηι (Xi-X)2 be the estimators of σ2. (i) Show that the MSE of S" is smaller than the MSE of S2 (ii) Find ElvS2] and suggest an unbiased estimator of σ. n be a random sample from N (μ, σ