Description

Introduction to Probability and Statistics for Engineers and Scientists provides a superior introduction to applied probability and statistics for engineering or science majors. Ross emphasizes the manner in which probability yields insight into statistical problems; ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage. As with the previous editions, Ross' text has tremendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications connect probability theory to everyday statistical problems and situations.

Key Features

  • Clear exposition by a renowned expert author
  • Real data examples that use significant real data from actual studies across life science, engineering, computing and business
  • End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material
  • 25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science
  • New additions to proofs in the estimation section
  • New coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.

Readership

Primary audience is scientists and engineers, upper level undergraduates and graduate students in engineering and the sciences

Table of Contents

  • Dedication
  • Preface
    • Organization and Coverage
    • Supplemental Materials
    • Acknowledgments
  • Chapter 1. Introduction to Statistics
    • 1.1 Introduction
    • 1.2 Data Collection and Descriptive Statistics
    • 1.3 Inferential Statistics and Probability Models
    • 1.4 Populations and Samples
    • 1.5 A Brief History of Statistics
    • Problems
  • Chapter 2. Descriptive Statistics
    • 2.1 Introduction
    • 2.2 Describing Data Sets
    • 2.3 Summarizing Data Sets
    • 2.4 Chebyshev’s Inequality
    • 2.5 Normal Data Sets
    • 2.6 Paired Data Sets and the Sample Correlation Coefficient
    • Problems
  • Chapter 3. Elements of Probability
    • 3.1 Introduction
    • 3.2 Sample Space and Events
    • 3.3 Venn Diagrams and the Algebra of Events
    • 3.4 Axioms of Probability
    • 3.5 Sample Spaces Having Equally Likely Outcomes
    • 3.6 Conditional Probability
    • 3.7 Bayes’ Formula
    • 3.8 Independent Events
    • Problems
  • Chapter 4. Random Variables and Expectation
    • 4.1 Random Variables
    • 4.2 Types of Random Variables
    • 4.3 Jointly Distributed Random Variables
    • 4.4 Expectation
    • 4.5 Properties of the Expected Value
    • 4.6 Variance
    • 4.7 Covariance and Variance of Sums of Random Variables
    • 4.8 Moment Generating Functions
    • 4.9 Chebyshev’s Inequality and the Weak Law of Large Numbers
    • Problems
  • Chapter 5. Special Random Variables
    • 5.1 The Bernoulli and Binomial Random Variables
    • 5.2 The Poisson Random Variable
    • 5.3 The Hypergeometric Random Variable
    • 5.4 The Uniform Random Variable
    • 5.5 Normal Random Variables
    • 5.6 Exponential Random Variables
    • 5.7 The Gamma Distribution
    • 5.8 Distributions Arising from the N

Details

No. of pages:
686
Language:
English
Copyright:
© 2014
Published:
Imprint:
Academic Press
Print ISBN:
9780123948113
Electronic ISBN:
9780123948427

Reviews

"...the book is intended for an introductory course, and assumes elementary calculus." --Gazette of the Australian Mathematical Society