Introductory Combinatorics
5th Edition
ISBN: 9780134689616
Author: Brualdi, Richard A.
Publisher: Pearson,
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Chapter 6, Problem 7E
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8. Show that, if {Xn, n ≥ 1) are independent random variables, then
sup X A) < ∞ for some A.
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6. Show that, for any random variable, X, and a > 0,
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P(x
Chapter 6 Solutions
Introductory Combinatorics
Ch. 6 - Prob. 1ECh. 6 - Find the number of integers between 1 and 10,000...Ch. 6 - Find the number of integers between 1 and 10,000...Ch. 6 - Prob. 4ECh. 6 - Determine the number of 10-combinations of the...Ch. 6 - A bakery sells chocolate, cinnamon, and plain...Ch. 6 - Determine the number of solutions of the equation...Ch. 6 - Determine the number of solutions of the equation...Ch. 6 - Determine the number of integral solutions of the...Ch. 6 - Let S be a multiset with k distinct objects with...
Ch. 6 - Determine the number of permutations of {1, 2, …,...Ch. 6 - Determine the number of permutations of {1, 2, ⋯,...Ch. 6 - Determine the number of permutations of {1, 2, …,...Ch. 6 - Determine a general formula for the number of...Ch. 6 - At a party, seven gentlemen check their hats. In...Ch. 6 - Use combinatorial reasoning to derive the...Ch. 6 - Determine the number of permutations of the...Ch. 6 - Verify the factorial formula
Ch. 6 - Using the evaluation of the derangement numbers as...Ch. 6 - Prob. 20ECh. 6 - Prove that Dn is an even number if and only if n...Ch. 6 - Show that the numbers Qn of Section 6.5 can be...Ch. 6 - (Continuation of Exercise 22.) Use the...Ch. 6 - What is the number of ways to place six...Ch. 6 - Prob. 25ECh. 6 - Count the permutations i1i2i3i4i5i6 of {1, 2, 3,...Ch. 6 - Prob. 27ECh. 6 - Prob. 28ECh. 6 - Prob. 29ECh. 6 - Prob. 30ECh. 6 - Prob. 31ECh. 6 - Prob. 32ECh. 6 - Prob. 33ECh. 6 - Prob. 34ECh. 6 - Consider the board with forbidden positions as...Ch. 6 - Prob. 38ECh. 6 - Prob. 39ECh. 6 - Consider the multiset X = {n1 · a1, n2 · a2, …, nk...
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- 15. This problem extends Problem 20.6. Let X, Y be random variables with finite mean. Show that 00 (P(X ≤ x ≤ Y) - P(X ≤ x ≤ X))dx = E Y — E X.arrow_forwardTheorem:- if A 2×2 prove i- At = 2 Re(Q) where Q₁ = (A - I) 21-12 Q2 = (A-2, 1) 72-71 if 21 = 2arrow_forward(b) Define a simple random variable. Provide an example.arrow_forward
- 17. (a) Define the distribution of a random variable X. (b) Define the distribution function of a random variable X. (c) State the properties of a distribution function. (d) Explain the difference between the distribution and the distribution function of X.arrow_forward16. (a) Show that IA(w) is a random variable if and only if A E Farrow_forward15. Let 2 {1, 2,..., 6} and Fo({1, 2, 3, 4), (3, 4, 5, 6}). (a) Is the function X (w) = 21(3, 4) (w)+711.2,5,6) (w) a random variable? Explain. (b) Provide a function from 2 to R that is not a random variable with respect to (N, F). (c) Write the distribution of X. (d) Write and plot the distribution function of X.arrow_forward
- 20. Define the o-field R2. Explain its relation to the o-field R.arrow_forward7. Show that An → A as n→∞ I{An} - → I{A} as n→ ∞.arrow_forward7. (a) Show that if A,, is an increasing sequence of measurable sets with limit A = Un An, then P(A) is an increasing sequence converging to P(A). (b) Repeat the same for a decreasing sequence. (c) Show that the following inequalities hold: P (lim inf An) lim inf P(A) ≤ lim sup P(A) ≤ P(lim sup A). (d) Using the above inequalities, show that if A, A, then P(A) + P(A).arrow_forward
- 19. (a) Define the joint distribution and joint distribution function of a bivariate ran- dom variable. (b) Define its marginal distributions and marginal distribution functions. (c) Explain how to compute the marginal distribution functions from the joint distribution function.arrow_forward18. Define a bivariate random variable. Provide an example.arrow_forward6. (a) Let (, F, P) be a probability space. Explain when a subset of ?? is measurable and why. (b) Define a probability measure. (c) Using the probability axioms, show that if AC B, then P(A) < P(B). (d) Show that P(AUB) + P(A) + P(B) in general. Write down and prove the formula for the probability of the union of two sets.arrow_forward
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