Chapter 3: Problem 80
A coin that comes up heads with probability \(p\) is flipped \(n\) consecutive times. What is the probability that starting with the first flip there are always more heads than tails that have appeared?
Chapter 3: Problem 80
A coin that comes up heads with probability \(p\) is flipped \(n\) consecutive times. What is the probability that starting with the first flip there are always more heads than tails that have appeared?
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Get started for freeA set of \(n\) dice is thrown. All those that land on six are put aside, and the others are again thrown. This is repeated until all the dice have landed on six. Let \(N\) denote the number of throws needed. (For instance, suppose that \(n=3\) and that on the initial throw exactly two of the dice land on six. Then the other die will be thrown, and if it lands on six, then \(N=2 .\) ) Let \(m_{n}=E[N]\). (a) Derive a recursive formula for \(m_{n}\) and use it to calculate \(m_{i}, i=2,3,4\) and to show that \(m_{5} \approx 13.024\). (b) Let \(X_{i}\) denote the number of dice rolled on the \(i\) th throw. Find \(E\left[\sum_{i=1}^{N} X_{i}\right]\).
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 \(\theta\).
The number of red balls in an urn that contains \(n\) balls is a random variable that is equally likely to be any of the values \(0,1, \ldots, n\). That is, $$ P\\{i \text { red, } n-i \text { non-red }\\}=\frac{1}{n+1}, \quad i=0, \ldots, n $$ The \(n\) balls are then randomly removed one at a time. Let \(Y_{k}\) denote the number of red balls in the first \(k\) selections, \(k=1, \ldots, n\) (a) Find \(P\left\\{Y_{n}=j\right\\}, j=0, \ldots, n\). (b) Find \(P\left\\{Y_{n-1}=j\right\\}, j=0, \ldots, n\) (c) What do you think is the value of \(P\left\\{Y_{k}=j\right\\}, j=0, \ldots, n ?\) (d) Verify your answer to part (c) by a backwards induction argument. That is, check that your answer is correct when \(k=n\), and then show that whenever it is true for \(k\) it is also true for \(k-1, k=1, \ldots, n\).
Consider \(n\) multinomial trials, where each trial independently results in outcome \(i\) with probability \(p_{i}, \sum_{i=1}^{k} p_{i}=1 .\) With \(X_{i}\) equal to the number of trials that result in outcome \(i\), find \(E\left[X_{1} \mid X_{2}>0\right]\)
In a knockout tennis tournament of \(2^{n}\) contestants, the players are paired and play a match. The losers depart, the remaining \(2^{n-1}\) players are paired, and they play a match. This continues for \(n\) rounds, after which a single player remains unbeaten and is declared the winner. Suppose that the contestants are numbered 1 through \(2^{n}\), and that whenever two players contest a match, the lower numbered one wins with probability \(p\). Also suppose that the pairings of the remaining players are always done at random so that all possible pairings for that round are equally likely. (a) What is the probability that player 1 wins the tournament? (b) What is the probability that player 2 wins the tournament? Hint: Imagine that the random pairings are done in advance of the tournament. That is, the first-round pairings are randomly determined; the \(2^{n-1}\) first-round pairs are then themselves randomly paired, with the winners of each pair to play in round 2; these \(2^{n-2}\) groupings (of four players each) are then randomly paired, with the winners of each grouping to play in round 3, and so on. Say that players \(i\) and \(j\) are scheduled to meet in round \(k\) if, provided they both win their first \(k-1\) matches, they will meet in round \(k\). Now condition on the round in which players 1 and 2 are scheduled to meet.
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