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2. Suppose i, ơ2. Let Y are iid normal random variables with nornnal distribution with unknown...
2. Suppose Yi,.. narei normal random variables with normal distribution with unknown mean and variance, μ...
2. Suppose Yi,.. narei normal random variables with normal distribution with unknown mean and variance, μ and or. Let Y-욤 Σ;..x. For this problem, you may not assume that n is large. (a) What is the distribution of Y? (b) what is the distribution of z-(yo), (en, (n-) (c) what is the distribution of (n-p? (d) What is the distribution of Justify your answer. (e) Let Zi-(ga)' + (-)' + (yo)", z2 = (속)' + (n-e)' what is the distribution...
Could I grab some help on problem 2? Thank you 2. Suppose Yi, Yn are iid...
Could I grab some help on problem 2? Thank you
2. Suppose Yi, Yn are iid normal random variables with normal distribution with unknown mean and variance, μ and ơ2. Let Y ni Y. For this problem you may not assume that n is large. n (a) What is the distribution of Y? (b) What is the distribution of Z = (yo)' + ( μ)' + (⅓ュ)? (o) What is the distribution of ta yis (d) What is the distribution...
Let X1,, Xn be independent and identically distributed random variables with unknown mean μ and unknown...
Let X1,, Xn be independent and identically distributed random variables with unknown mean μ and unknown variance σ2. It is given that the sample variance is an unbiased estimator of ơ2 Suggest why the estimator Xf -S2 might be proposed for estimating 2, justify your answer
4. Suppose Yi, Yn are iid randonn variables with E(X) = μ, Var(y)-σ2 < oo. For...
4. Suppose Yi, Yn are iid randonn variables with E(X) = μ, Var(y)-σ2 < oo. For large n, find the approximate distribution of p = n Σηι Yi, Be sure to name any theorems you used.
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0....
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0. In the last homework, you have computed the maximum likelihood estimator θ for θ in terms of the sample averages of the linear and quadratic means, i.e. Xn and X,and applied the CLT and delta method to find its asymptotic variance. In this problem, you will compute the asymptotic variance of θ via the Fisher Information....
8. Let Xi be iid N(μ, σ2) random variables. Define Y-Σ, Xi-Find the distribution of Y....
8. Let Xi be iid N(μ, σ2) random variables. Define Y-Σ, Xi-Find the distribution of Y. a.
Use this result without proof: if X and Y are two normal random variables with means...
Use this result without proof: if X and Y are two normal random variables with means ux and My respectively, and variances oź and oſ respectively, and Z = X+Y, Z is also a normal random variable with mean (ux + Hy) and variance (ox +og). a) Suppose Yı, Y2, Yz, Y4 and Y5 are all independent normal random variables, each with a mean of 1 and a variance of 5. What is the probability that (Y1 + 2Y2 +...
3. Let X1, . . . , Xn be iid random variables with mean μ and...
3. Let X1, . . . , Xn be iid random variables with mean μ and variance σ2. Let X denote the sample mean and V-Σ,(X,-X)2 a) Derive the expected values of X and V b) Further suppose that Xi,...,Xn are normally distributed. Let Anxn - ((a) be an orthogonal matrix whose first row is (mVm Y = (y, . . . ,%), and X = (Xi, , Xn), are (column) vectors. (It is not necessary to know aij for...
6. Let Xi 1,... ,Xn be a random sample from a normal distribution with mean u and variance ơ2 whi...
6. Let Xi 1,... ,Xn be a random sample from a normal distribution with mean u and variance ơ2 which are both unknown. (a) Given observations xi, ,Xn, one would like to obtain a (1-a) x 100% one-sided confidence interval for u as a form of L E (-00, u) the expression of u for any a and n. (b) Based on part (a), use the duality between confidence interval and hypothesis testing problem, find a critical region of size...
3. Let Xi, . . . , Xn be iid randoln variables with mean μ and...
3. Let Xi, . . . , Xn be iid randoln variables with mean μ and variance σ2. Let, X denote the sample mean and V-Σ, (X,-X)2. (a) Derive the expected values of X and V. (b) Further suppose that Xi,-.,X, are normally distributed. Let Anxn ((a)) an orthogonal matrix whose first rOw 1S be , ..*) and iet Y = AX, where Y (Yİ, ,%), ard X-(XI, , X.), are (column) vectors. (It is not necessary to know aij...
2. Suppose Yi,.. narei normal random variables with normal distribution with unknown mean and variance, μ and or. Let Y-욤 Σ;..x. For this problem, you may not assume that n is large. (a) What is the distribution of Y? (b) what is the distribution of z-(yo), (en, (n-) (c) what is the distribution of (n-p? (d) What is the distribution of Justify your answer. (e) Let Zi-(ga)' + (-)' + (yo)", z2 = (속)' + (n-e)' what is the distribution...
Could I grab some help on problem 2? Thank you
2. Suppose Yi, Yn are iid normal random variables with normal distribution with unknown mean and variance, μ and ơ2. Let Y ni Y. For this problem you may not assume that n is large. n (a) What is the distribution of Y? (b) What is the distribution of Z = (yo)' + ( μ)' + (⅓ュ)? (o) What is the distribution of ta yis (d) What is the distribution...
Let X1,, Xn be independent and identically distributed random variables with unknown mean μ and unknown variance σ2. It is given that the sample variance is an unbiased estimator of ơ2 Suggest why the estimator Xf -S2 might be proposed for estimating 2, justify your answer
4. Suppose Yi, Yn are iid randonn variables with E(X) = μ, Var(y)-σ2 < oo. For large n, find the approximate distribution of p = n Σηι Yi, Be sure to name any theorems you used.
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0. In the last homework, you have computed the maximum likelihood estimator θ for θ in terms of the sample averages of the linear and quadratic means, i.e. Xn and X,and applied the CLT and delta method to find its asymptotic variance. In this problem, you will compute the asymptotic variance of θ via the Fisher Information....
8. Let Xi be iid N(μ, σ2) random variables. Define Y-Σ, Xi-Find the distribution of Y. a.
Use this result without proof: if X and Y are two normal random variables with means ux and My respectively, and variances oź and oſ respectively, and Z = X+Y, Z is also a normal random variable with mean (ux + Hy) and variance (ox +og). a) Suppose Yı, Y2, Yz, Y4 and Y5 are all independent normal random variables, each with a mean of 1 and a variance of 5. What is the probability that (Y1 + 2Y2 +...
3. Let X1, . . . , Xn be iid random variables with mean μ and variance σ2. Let X denote the sample mean and V-Σ,(X,-X)2 a) Derive the expected values of X and V b) Further suppose that Xi,...,Xn are normally distributed. Let Anxn - ((a) be an orthogonal matrix whose first row is (mVm Y = (y, . . . ,%), and X = (Xi, , Xn), are (column) vectors. (It is not necessary to know aij for...
6. Let Xi 1,... ,Xn be a random sample from a normal distribution with mean u and variance ơ2 which are both unknown. (a) Given observations xi, ,Xn, one would like to obtain a (1-a) x 100% one-sided confidence interval for u as a form of L E (-00, u) the expression of u for any a and n. (b) Based on part (a), use the duality between confidence interval and hypothesis testing problem, find a critical region of size...
3. Let Xi, . . . , Xn be iid randoln variables with mean μ and variance σ2. Let, X denote the sample mean and V-Σ, (X,-X)2. (a) Derive the expected values of X and V. (b) Further suppose that Xi,-.,X, are normally distributed. Let Anxn ((a)) an orthogonal matrix whose first rOw 1S be , ..*) and iet Y = AX, where Y (Yİ, ,%), ard X-(XI, , X.), are (column) vectors. (It is not necessary to know aij...
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