A First Course in Probability
9th Edition
ISBN: 9780321794772
Author: Sheldon Ross
Publisher: PEARSON
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Textbook Question
Chapter 8, Problem 8.4P
Let
a. Use the Markov inequality to obtain a bound on
b. Use the central limit theorem to approximate
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Let X be a Poisson random variable with mean λ = 20. Estimate the probability P(X ≥25)
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(d) Central limit theorem.
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Chapter 8 Solutions
A First Course in Probability
Ch. 8 - Suppose that X is a random variable with mean and...Ch. 8 - From past experience, a professor knows that the...Ch. 8 - Use the central limit theorem to solve part (c) of...Ch. 8 - Let X1,...,X20 be independent Poisson random...Ch. 8 - Fifty numbers are rounded off to the nearest...Ch. 8 - A die is continually rolled until the total sum of...Ch. 8 - A person has 100 light bulbs whose lifetimes are...Ch. 8 - In Problem 8.7, suppose that it takes a random...Ch. 8 - If X is a gamma random variable with parameters...Ch. 8 - Civil engineers believe that W, the amount of...
Ch. 8 - Many people believe that the daily change of price...Ch. 8 - We have 100 components that we will put in use in...Ch. 8 - Student scores on exams given by a certain...Ch. 8 - A certain component is critical to the operation...Ch. 8 - An insurance company has 10.000 automobile...Ch. 8 - A.J. has 20 jobs that she must do in sequence,...Ch. 8 - Redo Example 5b under the assumption that the...Ch. 8 - Repeat part (a) of Problem 8.2 when it is known...Ch. 8 - A lake contains 4 distinct types of fish. Suppose...Ch. 8 - If X is a nonne9ative random variable with mean...Ch. 8 - Let X be a nonnegative random variable. Prove that...Ch. 8 - Prob. 8.22PCh. 8 - Let X be a Poisson random variable with mean 20....Ch. 8 - Prob. 8.24PCh. 8 - If X has variance 2, then , the positive square...Ch. 8 - If X has mean and standard deviation , the ratio...Ch. 8 - Compute the measurement signal-to-noise ratio-that...Ch. 8 - Let Zn,n1, be a sequence of random variables and...Ch. 8 - Prob. 8.5TECh. 8 - Prob. 8.6TECh. 8 - Prob. 8.7TECh. 8 - Explain why a gamma random variable with...Ch. 8 - Prob. 8.9TECh. 8 - If X is a Poisson random variable with mean , show...Ch. 8 - Prob. 8.11TECh. 8 - Prob. 8.12TECh. 8 - Prob. 8.13TECh. 8 - Prob. 8.14TECh. 8 - The number of automobiles sold weekly at a certain...Ch. 8 - Prob. 8.2STPECh. 8 - If E[X]=75E[Y]=75Var(X)=10var(Y)=12cov(X,Y)=3 give...Ch. 8 - Prob. 8.4STPECh. 8 - Prob. 8.5STPECh. 8 - Prob. 8.6STPECh. 8 - Prob. 8.7STPECh. 8 - Prob. 8.8STPECh. 8 - Prob. 8.9STPECh. 8 - A tobacco company claims that the amount of...Ch. 8 - Prob. 8.11STPECh. 8 - Prob. 8.12STPECh. 8 - The strong law of large numbers states that with...Ch. 8 - Each new book donated to a library must be...
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- Suppose that X₁, X2, X3 are independent and identically distributed random variables with distribution function: Fx (x) = 1 – 3¯ª for x ≥ 0 and Fx (x) = 0 for x 1).arrow_forwardLet X1, X2, X3 and X4 be exponential(1) random variables. Find the joint distribution of X1/(X1+X2+X3+X4) and (X1+X2)/(X1+X2+X3+X4) and (X1+X2+X3)/(X1+X2+X3+X4) using Jacobian method?arrow_forwardWhich statements are true? Select one or more: a. Markov’s inequality is only useful if I am interested in that X is larger than its expectation. b. Chebyshev’s inequality gives better bounds than Markov’s inequality. c. Markov’s inequality is easier to use. d. One can prove Chebyshev’s inequality using Markov’s inequality with (X−E(X))2.arrow_forward
- Suppose that X1, X2, X3 are independent and identically distributed random variables with distribution function: Fx (x) = 1 – 2 for x >0 and Fx (x) = 0 for x 1).arrow_forward8. Let X1, X20 be independent Poisson random variables with mean 1. (a) Use the Markov inequality to obtain a bound on P 20 {{x} Xi > 15 (b) Use the central limit theorem to approximate P 20 Xi> ¡ > 15}arrow_forwardQ1: Prove (a) Markov's Inequality for non-negative continuous random variables U. (b) Chebeshey's Inequality for continuous random variables W, without using Markov's inequality.arrow_forward
- Let Zm represent the outcome during the nth roll of a fair dice. Define the Markov chain X, to be the maximum outcome obtained so far after the nth roll, i.e., X, = max {Z1, Z2,..., Zn}. What is the transition probability p22 of the Markov chain {Xn}?arrow_forwardAnswer the following questions. Let X be a continuous random variable with P(X<0)=0. When E(X)=\mu exists, P(X\ge 3\mu) \le \frac{1}{(a)} by the Markov's inequality. What is (a)? Consider two random variables X and Z. The relationship between X and Z is given as X=1+2Z. Let Z be a random variable with moment generating function (mgf), M_Z(t) = (1-t)^{-3}, for t<1. What is the expectation of X?arrow_forwardWhich statements are true? Select one or more: a. Markov's inequality is only useful if I am interested in that X is larger than its expectation. b. Chebyshev's inequality gives better bounds than Markov's inequality. c. Markov's inequality is easier to use. d. One can prove Chebyshev's inequality using Markov's inequality with (X-E(X))-.arrow_forward
- Let X Exponential (3) a) Find the Markov upper bound for P(X>10). b) Find the Chebyshev upper bound for P(X>10). State which of the two bounds found is better. c) Find the Chernoff upper bound for P(X>10). Clearly state the allowable range for t. d) Let Zn be a RV from a Gamma(n, 3) distribution for n=1,2,... . What does converge in probability to? Please state both the value and the reasoning by which Z converges in probability to it. narrow_forwardThe random variables W1, W2,... are independent with common distribution k 1 2 3 4 Pr( W = k) 0.1 0.3 0.2 0.4 Let Xn max (W1,..., Wn) be the largest W observed to date. Determine the transition probability matrix for the Markov chain {Xn}.arrow_forwardLet X and Y are independent Poisson random variables such that E(X) = E(Y)=2. Let Z=X+Y. Compute P(X=2|Z=3).arrow_forward
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