a) false
b) false
c) false
d) true
e) true
f) false
g) Ch square test
h) improper
i) false
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 pa...
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....
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 Bookmark this page Setup: Suppose you have observations X1, X2, X3, X4, X5 which are i.i.d. draws from a Gaussian distribution with unknown mean u and unknown variance o? Given Facts: You are given the following: x=030, =1:1 Choose a test 1 point possible (graded, results hidden) To test...
Problem 1 Bookmark this page Problem 1. Linear Classification Consider a labeled training set shown in figure below: label = -1 label +1 O 1.(4) 1 point possible (graded, results hidden) What is the value of the margin attained? (Enter an exact answer or decimal accurate to at least 2 decimal places.) 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. 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....
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...
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 X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matrix vv1 , for some vector v ER 1point possible (graded) Let v = . (i.e., v is the normalized version of v). What is the variance of v X? (If applicable, enter trans(v) for the transpose v of v, and normv) for the norm |vll of a vector v.) Var (V STANDARD NOTATION SubmitYou have used 0...
3. Method of moments estimators Bookmark this page For each of the following distributions, give the method of moments estimator in terms of the sample averages Xn and X, assuming we have access to n i.i.d. observations X1,...,xn. In other words, express the parameters as functions of E [X1 and E[X] and then apply these functions to Xn and X (b) 1 point possible (graded) X; Poiss (), > 0, which means that each X1 has the pmf PX(X =...
11. Chi-Squared Test for a Family of Discrete Distributions A Bookmark this page In the problems on this page you will apply the goodness of fit test to determine whether or not a sample has a binomial distribution So far, we have used the x test to determine if our data had a categorical distribution with specific parameters (e.s uniform on an set). element For the problems on this page, we extend the discussion on x tests beyond what was...