Introduction to Probability and Statistics for Engineers and Scientists

Introduction to Probability and Statistics for Engineers and Scientists

6th Edition - September 11, 2020

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  • Author: Sheldon Ross
  • eBook ISBN: 9780128177471
  • Hardcover ISBN: 9780128243466

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Description

Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, uniquely emphasizes how probability informs statistical problems, thus helping readers develop an intuitive understanding of the statistical procedures commonly used by practicing engineers and scientists. Utilizing real data from actual studies across life science, engineering, computing and business, this useful introduction supports reader comprehension through a wide variety of exercises and examples. End-of-chapter reviews of materials highlight key ideas, also discussing the risks associated with the practical application of each material. In the new edition, coverage includes information on Big Data and the use of R. This book is intended for upper level undergraduate and graduate students taking a probability and statistics course in engineering programs as well as those across the biological, physical and computer science departments. It is also appropriate for scientists, engineers and other professionals seeking a reference of foundational content and application to these fields.

Key Features

  • Provides the author’s uniquely accessible and engaging approach as tailored for the needs of Engineers and Scientists
  • Features examples that use significant real data from actual studies across life science, engineering, computing and business
  • Includes new coverage to support the use of R
  • Offers new chapters on big data techniques

Readership

Undergraduate and graduate students in statistics, engineering or other sciences

Table of Contents

  • CHAPTER 1 Introduction to statistics

    CHAPTER 2 Descriptive statistics

    CHAPTER 3 Elements of probability

    CHAPTER 4 Random variables and expectation

    CHAPTER 5 Special random variables

    CHAPTER 6 Distributions of sampling statistics

    CHAPTER 7 Parameter estimation

    CHAPTER 8 Hypothesis testing

    CHAPTER 9 Regression

    CHAPTER 10 Analysis of variance

    CHAPTER 11 Goodness of fit tests and categorical data analysis

    CHAPTER 12 Nonparametric hypothesis tests

    CHAPTER 13 Quality control

    CHAPTER 14 Life testing

    CHAPTER 15 Simulation, bootstrap statistical methods, and permutation tests

    CHAPTER 16 Machine learning and big data

Product details

  • No. of pages: 704
  • Language: English
  • Copyright: © Academic Press 2020
  • Published: September 11, 2020
  • Imprint: Academic Press
  • eBook ISBN: 9780128177471
  • Hardcover ISBN: 9780128243466

About the Author

Sheldon Ross

Sheldon Ross
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.

Affiliations and Expertise

Professor, Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, USA

Ratings and Reviews

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  • Philippe R. Fri Oct 29 2021

    Quick and Simple

    Quick and Simple

  • David Mon Apr 19 2021

    Good book but paperback needed

    Very nice book but a student paperback cheaper version is needed immediately.