Introductory Combinatorics
5th Edition
ISBN: 9780134689616
Author: Brualdi, Richard A.
Publisher: Pearson,
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Chapter 5, Problem 27E
To determine
To prove: The combinatorial identity
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Let (5,3,-7) and = (2, -3, -6).
=
Compute the following:
u× u =
-4(u xv)
ux (-4v)
(+v) × v=
Let a = (4, -2, -7) and 6 = (2,5, 3).
(ã − ò) × (ã + b) =
4. Suppose that P(X = 1) = P(X = -1) = 1/2, that Y = U(-1, 1) and that X
and Y are independent.
(a) Show, by direct computation, that X + Y = U(-2, 2).
(b) Translate the result to a statement about characteristic functions.
(c) Which well-known trigonometric formula did you discover?
Chapter 5 Solutions
Introductory Combinatorics
Ch. 5 - Prob. 1ECh. 5 - Fill in the rows of Pascal’s triangle...Ch. 5 - Consider the sum of the binomial coefficients...Ch. 5 - Expand (x + y)5 and (x + y)6 using the binomial...Ch. 5 - Expand (2x − y)7 using the binomial theorem.
Ch. 5 - What is the coefficient of x5y13 in the expansion...Ch. 5 - Use the binomial theorem to prove that
Generalize...Ch. 5 - Use the binomial theorem to prove that
Ch. 5 - Evaluate the sum
Ch. 5 - Use combinatorial reasoning to prove the identity...
Ch. 5 - Use combinatorial reasoning to prove the identity...Ch. 5 - Let n be a positive integer. Prove that
(Hint:...Ch. 5 - Find one binomial coefficient equal to the...Ch. 5 - Prob. 14ECh. 5 - Prove, that for every integer n > 1,
Ch. 5 - By integrating the binomial expansion, prove that,...Ch. 5 - Prob. 17ECh. 5 - Evaluate the sum
Ch. 5 - Sum the series by observing that
and using the...Ch. 5 - Find integers a, b, and c such that
for all m....Ch. 5 - Prob. 21ECh. 5 - Prob. 22ECh. 5 - Prob. 23ECh. 5 - Prob. 24ECh. 5 - Use a combinatorial argument to prove the...Ch. 5 - Let n and k be integers with 1 ≤ k ≤ n. Prove...Ch. 5 - Let n and k be positive integers. Give a...Ch. 5 - Let n and k be positive integers. Give a...Ch. 5 - Find and prove a formula for
where the summation...Ch. 5 - Prove that the only antichain of S = {1, 2, 3, 4}...Ch. 5 - Prove that there are only two antichains of S =...Ch. 5 - Let S be a set of n elements. Prove that, if n is...Ch. 5 - Construct a partition of the subsets of {1, 2, 3,...Ch. 5 - In a partition of the subsets of {1,2, …, n} into...Ch. 5 - A talk show host has just bought 10 new jokes....Ch. 5 - Prove the identity of Exercise 25 using the...Ch. 5 - Use the multinomial theorem to show that, for...Ch. 5 - Use the multinomial theorem to expand (x1 + x2 +...Ch. 5 - Determine the coefficient of in the expansion...Ch. 5 - What is the coefficient of in the expansion of
Ch. 5 - Prob. 41ECh. 5 - Prob. 42ECh. 5 - Prove by induction on n that, for n a positive...Ch. 5 - Prove that
where the summation extends over all...Ch. 5 - Prove that
where the summation extends over all...Ch. 5 - Use Newton’s binomial theorem to approximate .
Ch. 5 - Use Newton’s binomial theorem to approximate...Ch. 5 - Use Theorem 5.6.1 to show that, if m and n are...Ch. 5 - Use Theorem 5.6.1 to show that, if m and n are...Ch. 5 - Prob. 50ECh. 5 - Let R and S be two partial orders on the same set...
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- 9. The concentration function of a random variable X is defined as Qx(h) = sup P(x ≤ X ≤x+h), h>0. x (a) Show that Qx+b (h) = Qx(h). (b) Is it true that Qx(ah) =aQx(h)? (c) Show that, if X and Y are independent random variables, then Qx+y (h) min{Qx(h). Qy (h)). To put the concept in perspective, if X1, X2, X, are independent, identically distributed random variables, and S₁ = Z=1Xk, then there exists an absolute constant, A, such that A Qs, (h) ≤ √n Some references: [79, 80, 162, 222], and [204], Sect. 1.5.arrow_forward29 Suppose that a mound-shaped data set has a must mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 6 and 12? b. About what percentage of the data should lie between 4 and 6? c. About what percentage of the data should lie below 4? 91002 175/1 3arrow_forward2,3, ample and rical t? the 28 Suppose that a mound-shaped data set has a mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 8 and 12? b. About what percentage of the data should lie above 10? c. About what percentage of the data should lie above 12?arrow_forward
- 27 Suppose that you have a data set of 1, 2, 2, 3, 3, 3, 4, 4, 5, and you assume that this sample represents a population. The mean is 3 and g the standard deviation is 1.225.10 a. Explain why you can apply the empirical rule to this data set. b. Where would "most of the values" in the population fall, based on this data set?arrow_forward30 Explain how you can use the empirical rule to find out whether a data set is mound- shaped, using only the values of the data themselves (no histogram available).arrow_forward5. Let X be a positive random variable with finite variance, and let A = (0, 1). Prove that P(X AEX) 2 (1-A)² (EX)² EX2arrow_forward
- 6. Let, for p = (0, 1), and xe R. X be a random variable defined as follows: P(X=-x) = P(X = x)=p. P(X=0)= 1-2p. Show that there is equality in Chebyshev's inequality for X. This means that Chebyshev's inequality, in spite of being rather crude, cannot be improved without additional assumptions.arrow_forward4. Prove that, for any random variable X, the minimum of EIX-al is attained for a = med (X).arrow_forward8. Recall, from Sect. 2.16.4, the likelihood ratio statistic, Ln, which was defined as a product of independent, identically distributed random variables with mean 1 (under the so-called null hypothesis), and the, sometimes more convenient, log-likelihood, log L, which was a sum of independent, identically distributed random variables, which, however, do not have mean log 1 = 0. (a) Verify that the last claim is correct, by proving the more general statement, namely that, if Y is a non-negative random variable with finite mean, then E(log Y) log(EY). (b) Prove that, in fact, there is strict inequality: E(log Y) < log(EY), unless Y is degenerate. (c) Review the proof of Jensen's inequality, Theorem 5.1. Generalize with a glimpse on (b).arrow_forward
- 2. Derive the component transformation equations for tensors shown be- low where [C] = [BA] is the direction cosine matrix from frame A to B. B[T] = [C]^[T][C]T 3. The transport theorem for vectors shows that the time derivative can be constructed from two parts: the first is an explicit frame-dependent change of the vector whereas the second is an active rotational change of the vector. The same holds true for tensors. Starting from the previous result, derive a version of transport theorem for tensors. [C] (^[T])[C] = dt d B dt B [T] + [WB/A]B[T] – TWB/A] (10 pt) (7pt)arrow_forwardUse the graph of the function y = f (x) to find the value, if possible. f(x) 8 7 6 Q5 y 3 2 1 x -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 -1 -2 -3 -4 -5 -6 -7 -8+ Olim f(z) x-1+ O Limit does not exist.arrow_forward3. Prove that, for any random variable X, the minimum of E(X - a)² is attained for a = EX. Provedarrow_forward
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