INTRODUCTION TO PROBABILITY AND STATISTICS FOR …

INTRODUCTION TO

PROBABILITY AND STATISTICS

FOR ENGINEERS AND SCIENTISTS

Fifth Edition

INTRODUCTION TO

PROBABILITY AND STATISTICS

FOR ENGINEERS AND SCIENTISTS

¡ö

Fifth Edition

¡ö

Sheldon M. Ross

University of Southern California, Los Angeles, USA

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Fifth Edition 2014

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ISBN: 978-0-12-394811-3

Library of Congress Cataloging-in-Publication Data

Ross, Sheldon M.

Introduction to probability and statistics for engineers and scientists / Sheldon M. Ross, Department of Industrial

Engineering and Operations Research, University of California, Berkeley. Fifth edition.

pages cm.

Includes index.

ISBN 978-0-12-394811-3

1. Probabilities. 2. Mathematical statistics. I. Title.

TA340.R67 2014

519.5¨Cdc23

2014011941

British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

For information on all Academic Press publications

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Printed and bound in the United States of America

For

Elise

Preface

The fifth edition of this book continues to demonstrate how to apply probability theory

to gain insight into real, everyday statistical problems and situations. As in the previous

editions, carefully developed coverage of probability motivates probabilistic models of

real phenomena and the statistical procedures that follow. This approach ultimately

results in an intuitive understanding of statistical procedures and strategies most often

used by practicing engineers and scientists.

Thisbookhasbeenwrittenfor anintroductory course in statisticsor inprobability and

statistics for students in engineering, computer science, mathematics, statistics, and the

natural sciences. As such it assumes knowledge of elementary calculus.

ORGANIZATION AND COVERAGE

Chapter 1 presents a brief introduction to statistics, presenting its two branches of descriptive and inferential statistics, and a short history of the subject and some of the people

whose early work provided a foundation for work done today.

The subject matter of descriptive statistics is then considered in Chapter 2. Graphs

and tables that describe a data set are presented in this chapter, as are quantities that

are used to summarize certain of the key properties of the data set.

To be able to draw conclusions from data, it is necessary to have an understanding

of the data¡¯s origination. For instance, it is often assumed that the data constitute a

¡°random sample¡± from some population. To understand exactly what this means and

what its consequences are for relating properties of the sample data to properties of the

entire population, it is necessary to have some understanding of probability, and that

is the subject of Chapter 3. This chapter introduces the idea of a probability experiment, explains the concept of the probability of an event, and presents the axioms of

probability.

Our study of probability is continued in Chapter 4, which deals with the important

concepts of random variables and expectation, and in Chapter 5, which considers some

special types of random variables that often occur in applications. Such random variables

as the binomial, Poisson, hypergeometric, normal, uniform, gamma, chi-square, t, and

F are presented.

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