Joint Distribution - Probability - Exam, Exams of Probability and Statistics

This is the Exam of Probability which includes Maximum, Hazard Rate Function, Continuous Random Variable, Density Function, Definition, Compute, Geometric, Geometric Random Variable etc. Key important points are: Joint Distribution, Continuous Random Variables, Compute, Test Engineer Discovered, Lifetime of an Equipment, Expected Lifetime, Variance, Parameter, Independent and Identically, Distributed

Typology: Exams

2012/2013

Uploaded on 02/21/2013

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Korea University
School of Information and Communications
CNCE363: Probability and Random Process
Spring Semester, 2012
Final exam (Closed book and open note)
June 19 Tuesday (in class)
Problem 1)[20pt] Let Xbe the number of 1’s and Ybe the number of 2’s that occur in nrolls
of a fair die. Compute Cov(X, Y ).
Problem 2)[20pt] The continuous random variables Xand Yhave joint distribution fX,Y (x, y) =
1
xfor 0 <y<x<1.
(a) Compute E[X] and E[Y].
(b) Compute Cov(X, Y ).
Problem 3)[20pt] A test engineer discovered that the CDF of the lifetime of an equipment in
years is given by
FX(x) = 1 ex/5if 0 <x<(1)
(a) What is the expected lifetime (i.e., expected value) of the equipment?
(b) What is the variance of the lifetime of the equipment?
Problem 4)[20pt] Let X1and X2be the independent and identically distributed exponential
random variables with the parameter λ(i.e. fZ(z) = λeλz for z0).
(a) Find out P(min(X1, X2)a).
(b) Find out P(max(X1, X2)a).
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Korea University

School of Information and Communications

CNCE363: Probability and Random Process

Spring Semester, 2012

Final exam (Closed book and open note)

June 19 Tuesday (in class)

Problem 1)[20pt] Let X be the number of 1’s and Y be the number of 2’s that occur in n rolls of a fair die. Compute Cov(X, Y ).

Problem 2)[20pt] The continuous random variables X and Y have joint distribution fX,Y (x, y) = 1 x for 0^ < y < x <^ 1. (a) Compute E[X] and E[Y ]. (b) Compute Cov(X, Y ).

Problem 3)[20pt] A test engineer discovered that the CDF of the lifetime of an equipment in years is given by

FX (x) = 1 − e−x/^5 if 0 < x < ∞ (1)

(a) What is the expected lifetime (i.e., expected value) of the equipment? (b) What is the variance of the lifetime of the equipment?

Problem 4)[20pt] Let X 1 and X 2 be the independent and identically distributed exponential random variables with the parameter λ (i.e. fZ (z) = λe−λz^ for z ≤ 0). (a) Find out P (min(X 1 , X 2 ) ≤ a). (b) Find out P (max(X 1 , X 2 ) ≤ a).

Problem 5)[20pt] The joint probability density function of X and Y is given by

f (x, y) = c(y^2 − x^2 )e−y^ − y ≤ x ≤ y, 0 ≤ y ≤ ∞ (2)

(a) Find c. (b) Find the marginal densities of X and Y.

Problem 6)[20pt] An urn contains 5 white and 10 black balls. A fair die is rolled and that number of balls is chosen from the urn. What is the probability that all of the balls selected are white? What is the conditional probability that the die landed on 3 if all the balls selected are white?