Chapter 6: Q. 6.35 (page 277)
If X and Y are independent standard normal random variables, determine the joint density function of
Then use your result to show that has a Cauchy distribution.
Short Answer
The joint density function of u and v
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Chapter 6: Q. 6.35 (page 277)
If X and Y are independent standard normal random variables, determine the joint density function of
Then use your result to show that has a Cauchy distribution.
The joint density function of u and v
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The joint probability density function of X and Y is given by
(a) Verify that this is indeed a joint density function.
(b) Compute the density function of X.
(c) Find P{X > Y}.
(d) Find P{Y > 1 2 |X < 1 2 }.
(e) Find E[X].
(f) Find E[Y].
Consider independent trials, each of which results in outcome i, i = 0, 1, ... , k, with probability pi, k i=0 pi = 1. Let N denote the number of trials needed to obtain an outcome that is not equal to 0, and let X be that outcome.
(a) Find P{N = n}, n Ú 1.
(b) Find P{X = j}, j = 1, ... , k.
(c) Show that P{N = n, X = j} = P{N = n}P{X = j}.
(d) Is it intuitive to you that N is independent of X?
(e) Is it intuitive to you that X is independent of N?
If X, Y, and Z are independent random variables having identical density functions derive the joint distribution of .
Let X and Y be independent uniform (0, 1) random variables.
(a) Find the joint density of U = X, V = X + Y.
(b) Use the result obtained in part (a) to compute the density function of V
Let be independent standard normal random variables, and let
(a) What is the conditional distribution of Sn given that for k = 1, ... , n?
(b) Show that, for 1 … k … n, the conditional distribution of given that
Sn = x is normal with mean xk/n and variance k(n − k)/n.
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