A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN: 9780134753119
Author: Sheldon Ross
Publisher: PEARSON
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Chapter 8, Problem 8.23P

Let X be a Poisson random variable with mean 20.

a. Use the Markov inequality to obtain an upper bound on p = P { X 26 }

b. Use the one-sided Chebyshev inequality to obtain an upper bound on p.

c. Use the Chernoff bound to obtain an upper bound on p.

d. Approximate p by making use of the central limit theorem.

e. Determine p by running an appropriate program.

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Students have asked these similar questions
Which 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.
Which 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))-.
Markov’s inequality states that Select one:   a. P(|X|≥t)≤E(X)/t for all random variables X and all t≥0.   b. P(|X|≤t)≤E(X)/t for all random variables X and all t≥0.   c. P(X≥t)≤E(X)/t for all non-negative random variables X and all t≥0.   d. P(X≤t)≤E(X)/t for all non-negative random variables X and all t≥0.

Chapter 8 Solutions

A First Course in Probability (10th Edition)

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