4.
Setup:
Suppose you have observations X1,X2,X3,X4,X5 which are i.i.d. draws from a Gaussian distribution with unknown mean μ and unknown variance σ2.
Given Facts:
You are given the following:
15∑i=15Xi=0.90,15∑i=15X2i=1.31 |
4. Setup: Suppose you have observations X1,X2,X3,X4,X5 which are i.i.d. draws from a Gaussian distribution with...
Problem 4 True or False A Bookmark this page Instructions: Be very careful with the multiple choice questions below. Some are "choose all that apply," and many tests your knowledge of when particular statements apply As in the rest of this exam, only your last submission will count. 1 point possible (graded, results hidden) The likelihood ratio test is used to obtain a test with non-asymptotic level o True O False Submit You have used 0 of 3 attempts Save...
As on the previous page, let Xi,...,Xn be i.i.d. with pdf where >0 2 points possible (graded, results hidden) Assume we do not actually get to observe X, . . . , Xn. to estimate based on this new data. Instead let Yİ , . . . , Y, be our observations where Yi-l (X·S 0.5) . our goals What distribution does Yi follow? First, choose the type of the distribution: Bernoulli Poisson Norma Exponential Second, enter the parameter of...
1 Bookmark this page Setup: For all problems on this page, suppose you have data X],...,x . N (0,1) that is a random sample of identically and independently distributed standard normal random variables. Useful facts: The following facts might be useful: For a standard normal random variable X1, we have: E[X] =0, E[X{1=1, E(X) = 3. Sample mean 1.5 points possible (graded, results hidden) Consider the sample mean: X = x + X2+...+X,). What are the mean E [Xn] and...
Consider a sample of i.i.d. random variables X1,..., X, and assume their common density is given by fo(a) = exp (3) 1(220), where is an unknown parameter Consider the following set of hypotheses: H:0=1 and H:0 1. You will perform the likelihood ratio test at significance level 7% for these hypotheses. Assume that the sample size is n=500. You observe that • The sample mean is 1 , X; = 0.86: • The (biased) sample variance is 15. (X- Xn)...
in a Bayesian view. Consider the prior π(a)-1 for all a e R Consider a Gaussian linear model Y = aX+ E Determine whether each of the following statements is true or false. π(a) a uniform prior. (1) (a) True (b) False L(Y=y14=a,X=x) (2) π(a) is a jeffreys prior when we consider the likelihood (where we assume xis known) (a) True (b)False Y-XB+ σε where ε E R" is a random vector with Consider a linear regression model E[ε1-0, E[eErJ-1....
You have five coins in your pocket. You know a priori that one coin gives heads with probability 0.4, and the other four coins give heads with probability 0.7 You pull out one of the five coins at random from your pocket (each coin has probability 릊 of being pulled out), and you want to find out which of the two types of coin it is. To that end, you flip the coin 6 times and record the results X1...
Suppose you have a random sample {X1, X2, X3} of size n = 3. Consider the following three possible estimators for the population mean u and variance o2 Дi 3D (X1+ X2+ X3)/3 Ti2X1/4 X2/2 X3/4 Дз — (Х+ X,+ X3)/4 (a) What is the bias associated with each estimator? (b) What is the variance associated with each estimator? (c) Does the fact that Var(i3) < Var(1) contradict the statement that X is the minimum variance unbiased estimator? Why or...
1. Implicit hypothesis testing Homework due Jul 29, 2020 07:59 HKT Bookmark this page Given n i.i.d. samples X1,..., X, N (u,02) with p ER and op > 0, we want to find a test with asymptotic level 5% for the hypotheses (7.1) Η :μοσ vs H, :μ<σ. (a) 1 point possible (graded) As a first step, define the maximum likelihood estimators ů = Xn, 32 = (X: – 8.)? Give a function g(x,y) such that P 9(î, o?) -0....
Suppose you have a sample of n independent observations X1,X2,...,Xn from a normal population with mean μ (known) and variance σ2 (unknown). (a) Find the ML estimator of σ2 . (b) Show that the ML estimator in (a) is a consistent estimator of θ. (c) Find a sufficient statistic for σ2. (d) Give a MVUE for θ based on the sufficient statistic.
We have n observations that are i. i. d. from a Normal distribution with mean 0 anod unknown variance. We want to test using a Generalized Likelihood Ratio Test. Calculate the test statistic T for the GLRT. You can assume that the MLE for the variance is Tn 62 2