X1 and X2 are binary indicators of failure for two parts of a machine. Independent tests have shown that X1~Bernoulli(1/2) and X2~Bernoulli(1/3). Y1 and Y2 are binary indicators of two system failures. We know that Y1=1 if both X1=1 and X2=1 and Y1=0 otherwise. Also, Y2=1 if either X1=1 or X2=1 and Y2=0 otherwise.
a.) What is the probability that X1=1 and X2=1 given Y1=1?
b.) What is the probability that X1=1 and X2=1 given Y2=1?
c.) What is the probability that X1=1 given Y1=1?
d.) What is the probability that X1=1 given Y2=1?
X1 and X2 are binary indicators of failure for two parts of a machine. Independent tests...
(2) Given two independent variables X1 and X2 having Bernoulli distribution with parameter p=1/3, let Y1 = 2X1 and Y2 = 2X2. Then A E[Y1 · Y2] = 2/9 BE[Y1 · Y2] = 4/9 C P[Y1 · Y2 = 0) = 1/9 D P[Y1 · Y2 = 0) = 2/9 (3) Let X and Y be two independent random variables having gaussian (normal) distribution with mean 0 and variance equal 2. Then: A P[X +Y > 2] > 0.5 B...
Q2 Suppose X1, X2, X3 are independent Bernoulli random variables with p = 0.5. Let Y; be the partial sums, i.e., Y1 = X1, Y2 = X1 + X2, Y3 = X1 + X2 + X3. 1. What is the distubution for each Yį, i = 1, 2, 3? 2. What is the expected value for Y1 + Y2 +Yz? 3. Are Yį and Y2 independent? Explain it by computing their joint P.M.F. 4. What is the variance of Y1...
Let X1, X2, X3 be independent Binomial(3,p) random variables. Define Y1 = X1 + X3 and Y2 = X2 + X3. Define Z1 = 1 if Y1 = 0; and 0 otherwise. Define Z2 = 1 if Y2 = 0; and 0 otherwise. As Z1 and Z3 both contain X3, are Z1 and Z3 independent? What is the marginal PMF of Z1 and Z2 and joint PMF of (Z1, Z2) and what is the correlation coefficient between Z1 and Z2?
Let (X1, Y1) and (X2, Y2) be independent and identically distributed continuous bivariate random variables with joint probability density function: fX,Y (x,y) = e-y, 0 <x<y< ; =0 , elsewhere. Evaluate P( X2>X1, Y2>Y1) + P (X2 <X1, Y2<Y1) .
Suppose X1,X2,…,Xn represent the outcomes of n independent
Bernoulli trials, each with success probability p. Note that we can
write the Bernoulli distribution as:
Suppose X1 2 X, represent the outcomes of n independent Bernou i als, each with success probabil ,p. Note that we can writ e the Bernoulǐ distribution as 0,1 otherwise Given the Bernoulli distributional family and the iid sample of X,'s, the likelihood function is: -1 a. Find an expression for p, the MLE of p...
Let Y1, Y2, and Y3 be independent, N(0, 1)-distributed random variables, and set X1 = Y1 − Y3, X2 = 2Y1 + Y2 − 2Y3, X3 = −2Y1 + 3Y3.Determine the conditional distribution of X2 given that X1 + X3 = x.
Let X1 and X2 be independent and have the same pdf that is given by f(t)=2t when 0 < t < 1 and zero otherwise. Find the probability P(X1/X2 < 1/2).
two random variables x1 and x2 have a joint probability density function f(x1,x2)={x1+x2, 0<x1<1, 0<x2<1 0, otherwise what is the marginal distribution of x1 and x2
Let X1 and X2 be two independent standard normal random variables. Define two new random variables as follows: Y-Xi X2 and Y2- XiBX2. You are not given the constant B but it is known that Cov(Yi, Y2)-0. Find (a) the density of Y (b) Cov(X2, Y2)
5. Let X1 and X2 be two independent standard normal random variables. Define two new random variables as follows: Yı = X1 + X2 and ½ = X1 + ßX2. You are not given the constant β but it is known that Cov(Yi,Y) = 0. Find (a) the density of Y2 (b) Cov(Xy½),