Chapter 6: Q.6.59 (page 274)
If X, Y, and Z are independent random variables having identical density functions derive the joint distribution of .
Short Answer
Joint distribution function :
Chapter 6: Q.6.59 (page 274)
If X, Y, and Z are independent random variables having identical density functions derive the joint distribution of .
Joint distribution function :
All the tools & learning materials you need for study success - in one app.
Get started for freeIf are independent random variables that are uniformly distributed over, compute the probability that the largest of the three is greater than the sum of the other two.
If U is uniform on and Z, independent of U, is exponential with rate , show directly (without using the results of Example b) that X and Y defined by
are independent standard normal random variables.
If X and Y are independent random variables both uniformly distributed over , find the joint density function of .
Suppose that W, the amount of moisture in the air on a given day, is a gamma random variable with parameters (t, β). That is, its density is f(w) = βe−βw(βw)t−1/(t), w > 0. Suppose also that given that W = w, the number of accidents during that day—call it N—has a Poisson distribution with mean w. Show that the conditional distribution of W given that N = n is the gamma distribution with parameters (t + n, β + 1)
A man and a woman agree to meet at a certain location about 12:30 p.m. If the man arrives at a time uniformly distributed between 12:15 and 12:45, and if the woman independently arrives at a time uniformly distributed between 12:00 and 1 p.m., find the probability that the first to arrive waits no longer than 5 minutes. What is the probability that the man arrives first?
What do you think about this solution?
We value your feedback to improve our textbook solutions.