9th Edition

ISBN: 9780321794772

Author: Sheldon Ross

Publisher: PEARSON

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Textbook Question

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.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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Chapter 8, Problem 8.22P

Chapter 8, Problem 8.24P

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Chapter 8 Solutions

A First Course in Probability

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Solution Summary: The author explains the expression for the upper bound by the Markov inequality. The required value is 0.769.

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