Given X = {0, 1} with X = 1 indicating disease. Given their status, a diagnostic test returns a classification of Y = {0, 1} with Y= 1 indicating a positive result: X~ Ber(p) Y | X~ Ber(px) Recall that the pmf of a generic Ber(π) random variable, W, is fw (w) = pw(1 − p)¹-w 0 < π≤ 1 for w = {0, 1} and fw (w) = 0 elsewhere. 1. Find the marginal expectation E[Y] in terms of p, p₁, and po. 2. Find the Cov(Y, X) in terms of p, p₁, and po. 3. Find an expression for P(X = 1 | Y = y) only in terms of y = p², and p. 4. Prove that the conditional variance of X is V[X | Y = y] = P(X = 1 | Y = y)(1 − P(X = 1 | Y = y))
Given X = {0, 1} with X = 1 indicating disease. Given their status, a diagnostic test returns a classification of Y = {0, 1} with Y= 1 indicating a positive result: X~ Ber(p) Y | X~ Ber(px) Recall that the pmf of a generic Ber(π) random variable, W, is fw (w) = pw(1 − p)¹-w 0 < π≤ 1 for w = {0, 1} and fw (w) = 0 elsewhere. 1. Find the marginal expectation E[Y] in terms of p, p₁, and po. 2. Find the Cov(Y, X) in terms of p, p₁, and po. 3. Find an expression for P(X = 1 | Y = y) only in terms of y = p², and p. 4. Prove that the conditional variance of X is V[X | Y = y] = P(X = 1 | Y = y)(1 − P(X = 1 | Y = y))
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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