Introduction to Probability and Statistics for Engineers and Scientists

Introduction to Probability and Statistics for Engineers and Scientists

by Sheldon M. Ross
Introduction to Probability and Statistics for Engineers and Scientists

Introduction to Probability and Statistics for Engineers and Scientists

by Sheldon M. Ross

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Overview

Reviews fundamental concepts and applications of probability and statistics. After a general overview, it considers special types of random variables, using examples which illustrate their wide variety of applications. Also examines their calculation and presents computer programs that calculate the probability distribution, and the inverses of binomial, poisson, normal, t, F, and Chi-square distributions. Coverage includes such topics as the sample mean, sample variance, sample median, as well as histograms, empirical distribution functions, and stem-and-leaf plots. A program for computing sample mean and sample variance for a given data set is included. A diskette of 35 programs for the IBM PC is available, giving exact answers or approximations where appropriate.

Product Details

ISBN-13: 9780123948427
Publisher: Elsevier Science
Publication date: 08/14/2014
Sold by: Barnes & Noble
Format: eBook
Pages: 686
File size: 18 MB
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About the Author

Dr. Sheldon M. Ross is a professor in the Department of Industrial and Systems Engineering at the University of Southern California. He received his PhD in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, a Fellow of INFORMS, and a recipient of the Humboldt US Senior Scientist Award.

Table of Contents

Elements of Probability.
Random Variables and Expectation.
Special Random Variables.
Sampling.
Parameter Estimation.
Hypothesis Testing.
Regression.
Analysis of Variance.
Goodness of Fit and Nonparametric Testing.
Life Testing.
Quality Control.
Simulation.
Appendix of Programs.
Appendix of Tables.
Index.

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A proven text reference for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for professionals seeking a reference of foundational content and application to these fields.

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