[20 pts] (Fron Stock and Watson 2.25) Let xi, ,xn denote a sequence of numbers, yi,...
- Let {Xn} denote a sequence of iid random variables such that P(Xi = 1) = P(X1 = -1) = 1/2. Let Sn = X1 + X2 + ... + xn. (a) Find ES, and var(Sn); (b) Show that Sn is a martingale.
f Squares and Properties of Estimators o. Let xi yi denote two series ofn numbers xi: i-1,2...), tyi: i 1,2...n) Assume that xi s drawn from a distribution that is NOHm σ) Show that the sample mean i ΣΙ-1 χί has a variance of σ/n carefully stating any required assunmptions at each step. Is the sample mean an unbiased estimator of u,? 1. ii. The following results are useful when working with linear regressions. Show that: 2 iii. Show that:...
4. (20 pts) Let {xn} be a Cauchy sequence. Show that a) (5 pts) {xn} is bounded. Hint: See Lecture 4 notes b) (5 pts) {Jxn} is a Cauchy sequence. Hint: Use the following inequality ||x| - |y|| < |x - y|, for all x, y E R. _ subsequence of {xn} and xn c) (5 pts) If {xnk} is a See Lecture 4 notes. as k - oo, then xn OO as n»oo. Hint: > d) (5 pts) If...
3. Let {x1, x2,...,xn} be a list of numbers and let ¯ x denote the average of the list. Let a and b be two constants, and for each i such that 1 ≤ i ≤ n, let yi = axi + b. Consider the new list {y1,y2,...,yn}, and let the average of this list be ¯ y. Prove a formula for ¯ y in terms of a, b, and ¯ x. 4. Let n be a positive integer. Consider...
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...
Suppose Xi, X2, ,Xn is an iid N(μ, c2μ2 sample, where c2 is known. Let μ and μ denote the method of moments and maximum likelihood estimators of μ, respectively. (a) Show that ~ X and μ where ma = n-1 Σηι X? is the second sample (uncentered) moment. (b) Prove that both estimators μ and μ are consistent estimators. (c) Show that v n(μ-μ)-> N(0, σ ) and yM(^-μ)-+ N(0, σ ). Calculate σ and σ . Which estimator...
Let Xi, X2, , xn be independent Normal(μ, σ*) random variables. Let Yn = n Ση1Xi denote a sequence of random variables (a) Find E(%) and Var(%) for all n in terms of μ and σ2. (b) Find the PDF for Yn for all n c) Find the MGF for Y for all n
Let Xi, , xn be a randon sannple fron f,(z0)-e-(z-0),0 є (-00,00), z > θ a. Show that X(1) is a complete statistic for θ. Hint: First find the PDF of XI) b. Show that the sample variance S is an ancllar statistic,and use this result to show that Xa) and S2 are independent.
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...
(a) Let C be the line segment on the plane that starts from a point (xi,yi) to a different point (x2,Y2). Show that (b) Consider a simple polygon whose vertices are (2.1 , Й), (T2, Уг), . . . , (Xn, yn) if its boundary is traversed counterclockwise. Use Green's theorem to show that the area of this polygon is
(a) Let C be the line segment on the plane that starts from a point (xi,yi) to a different point...