Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

In the match problem, say that \((i, j), i

Short Answer

Expert verified
(a) The expected number of pairs is \(E(pairs)=\binom{n}{2}\times\frac{1}{(n-1)(n-2)}\). (b) The recursive formula for the probability of having no pairs is \(Q_n = \frac{1}{n}\sum_{j=1}^{n-1} Q_{n-j}\). (c) The probability of having no pairs with 8 people, \(Q_8\), is \(\frac{1}{40320}\).

Step by step solution

01

(a) Expected Number of Pairs

To find the expected number of pairs, we should determine the total number of pairings and then the probability of any single pair being matched correctly. After that, we can calculate the expected number of pairs. First, let's determine the total number of pairings possible. This can be calculated as the number of permutations of the set of n people/indices, which is given by \(n!\). Next, let's determine the probability of a single pair (i, j) being matched correctly. For a pair (i, j) to be matched correctly, i must choose j's hat, and j must choose i's hat. The probability of this happening is, therefore, \(\frac{1}{n-1}\times\frac{1}{n-2}\). Now, since there are \(\binom{n}{2}\) possible pairs, the expected number of pairs can be calculated as the product of the probability of a single pair being matched and the number of pairs, which is: \(E(pairs)=\binom{n}{2}\times\frac{1}{(n-1)(n-2)}\)
02

(b) Recursive Formula for Probability of Having No Pairs

To derive a recursive formula for the probability of having no pairs, we can follow this process: Consider a cyclic permutation of the members. 1. If the cycle has length n, then no pairs are formed, and this occurs with the probability of \(Q_n\). 2. If the cycle has length smaller than n, say j, we remove this cycle from the permutation. Now we have \(n-j\) remaining elements, and their configuration has a probability of \(Q_{n-j}\). This means that the probability of having no pairs in a permutation of n elements can be expressed as the sum of the probabilities of all the configurations involving cycles with length smaller than n. So, we have: \(Q_n = \frac{1}{n}\sum_{j=1}^{n-1} Q_{n-j}\)
03

(c) Calculate Q8

To find \(Q_8\), we will use the recursive formula derived in part (b) and calculate the value of \(Q_n\) for each n smaller than 8: \(Q_1 = 1\) (Trivial Case) \(Q_2 = \frac{1}{2}(Q_1) = \frac{1}{2}\) \(Q_3 = \frac{1}{3}(Q_2) = \frac{1}{3}\times\frac{1}{2} = \frac{1}{6}\) \(Q_4 = \frac{1}{4}(Q_3) = \frac{1}{4}\times\frac{1}{6} = \frac{1}{24}\) \(Q_5 = \frac{1}{5}(Q_4) = \frac{1}{5}\times\frac{1}{24} = \frac{1}{120}\) \(Q_6 = \frac{1}{6}(Q_5) = \frac{1}{6}\times\frac{1}{120} = \frac{1}{720}\) \(Q_7 = \frac{1}{7}(Q_6) = \frac{1}{7}\times\frac{1}{720} = \frac{1}{5040}\) Now, using the same recursive formula, we can find \(Q_8\): \(Q_8 = \frac{1}{8}(Q_7) = \frac{1}{8}\times\frac{1}{5040}\) \(Q_8 = \frac{1}{40320}\) So, the probability of having no pairs when there are 8 people is \(\frac{1}{40320}\).

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Independent trials, resulting in one of the outcomes \(1,2,3\) with respective probabilities \(p_{1}, p_{2}, p_{3}, \sum_{i=1}^{3} p_{i}=1\), are performed. (a) Let \(N\) denote the number of trials needed until the initial outcome has occurred exactly 3 times. For instance, if the trial results are \(3,2,1,2,3,2,3\) then \(N=7\) Find \(E[N]\). (b) Find the expected number of trials needed until both outcome 1 and outcome 2 have occurred.

\(A, B\), and \(C\) are evenly matched tennis players. Initially \(A\) and \(B\) play a set, and the winner then plays \(C\). This continues, with the winner always playing the waiting player, until one of the players has won two sets in a row. That player is then declared the overall winner. Find the probability that \(A\) is the overall winner.

Let \(X\) be exponential with mean \(1 / \lambda ;\) that is, $$ f_{X}(x)=\lambda e^{-\lambda x}, \quad 01]\)

In the list problem, when the \(P_{i}\) are known, show that the best ordering (best in the sense of minimizing the expected position of the element requested) is to place the elements in decreasing order of their probabilities. That is, if \(P_{1}>P_{2}>\cdots>P_{n}\) show that \(1,2, \ldots, n\) is the best ordering.

Let \(X_{1}, \ldots, X_{n}\) be independent random variables having a common distribution function that is specified up to an unknown parameter \(\theta\). Let \(T=T(\mathrm{X})\) be a function of the data \(\mathrm{X}=\left(X_{1}, \ldots, X_{n}\right) .\) If the conditional distribution of \(X_{1}, \ldots, X_{n}\) given \(T(\mathrm{X})\) does not depend on \(\theta\) then \(T(\mathrm{X})\) is said to be a sufficient statistic for \(\theta .\) In the following cases, show that \(T(\mathbf{X})=\sum_{i=1}^{n} X_{i}\) is a sufficient statistic for \(\theta\). (a) The \(X_{i}\) are normal with mean \(\theta\) and variance \(1 .\) (b) The density of \(X_{i}\) is \(f(x)=\theta e^{-\theta x}, x>0\). (c) The mass function of \(X_{i}\) is \(p(x)=\theta^{x}(1-\theta)^{1-x}, x=0,1,0<\theta<1\). (d) The \(X_{i}\) are Poisson random variables with mean \(\theta\).

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free