6. Let X1 and X2 be independent and identically distributed random variables with joint mgfMx,x, (t1, t2) = [(1 – t,)(1 – t2)]¯1.%3D6.1 Give the marginal mgf of X2, mx, (t2).6.2 Give the mgf of Y = X, + X2, my(t).

Answered: Image /qna-images/answer/628c1b36-26d8-43a0-b853-cd4e1739af93.jpg

Answered: 6. Let X1 and X2 be independent and…

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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3.7. Consider the performance function Y = 3x1-2x2 where Xi and X2 are both normally distributed random variables with Ax' = 16.6 0% 2.45 μΧ2 = 18.8 ơx.-2.83 The two variables are correlated, and the covariance is equal to 2.0. Determine the probability of failure if failure is defined as the state when Y 0 3.8. The resistance (or capacity) R of a member is to be modeled using R = R,MPF where Rn is the nominal value of the capacity determined using code procedures and M, P, and Fare random variables that account for various uncertainties in the capacity. If M, P, and F are all lognormal random variables, determine the mean and variance of R in terms of the means and variances of M, P, and F.
Question 2. Show that, for a simple linear regression, R² = ry, where R² is the coefficient of determination and rxy is the sample correlation between Y and X. Hint: Σ" (Υ - Y)2 Σ1(Y₁-Y)²¹ SxY √SXXSYY' where Sxy = 1 (X; — X)(Y; — Y), Sxx = ₁1(X; - X)², Syy = ₁₁(Y₁ - Y)². R² = "XY =
(b) Let X₁, X₂, X3 be uncorrelated random variables, having the same variance ². Consider the linear transformations Y₁ = X₁ + X₂, Y₂ = X₁ + X3 and Y3 = X₂ + X3 . Find the correlations of Yi, Y; for i #j. (5 marks)
Consider the one-way analysis of variance model Xij = µ + a; + Eij, i= 1,.., m, j= 1,..., ni, where ɛij ~ N(0,0²) are independent. Let n= n1 + · ·+ nm, ... ni 1 ni 1 X;. >Xii for i = 1,..., m, and X. = - ΣΣΧ. ni j=1 i=1 j=1 (a) Show that SS(TO) = SS(T) + SS(E), where SS(TO) = E E i=12j=1 (Xij – X..)², m m ni SS(T) Σι (X.-Χ.) and SS(E) -ΣΣ (Χ- X.) . i=1 i=1 j=1
Page 263, 4.4.8
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6. Let X1 and X2 be independent and identically distributed random variables with joint mgf Mx,x, (t1, t2) = [(1 – t,)(1 – t2)]¯1. %3D 6.1 Give the marginal mgf of X2, mx, (t2). 6.2 Give the mgf of Y = X, + X2, my(t).