Probability, Statistics, and Reliability for Engineers and Scientists 3rd Edition

In a technological society, virtually every engineer and scientist needs to be able to collect, analyze, interpret, and properly use vast arrays of data. This means acquiring a solid foundation in the methods of data analysis and synthesis. Understanding the theoretical aspects is important, but learning to properly apply the theory to real-world problems is essential.

Probability, Statistics, and Reliability for Engineers and Scientists, Third Edition introduces the fundamentals of probability, statistics, reliability, and risk methods to engineers and scientists for the purposes of data and uncertainty analysis and modeling in support of decision making.

The third edition of this bestselling text presents probability, statistics, reliability, and risk methods with an ideal balance of theory and applications. Clearly written and firmly focused on the practical use of these methods, it places increased emphasis on simulation, particularly as a modeling tool, applying it progressively with projects that continue in each chapter. This provides a measure of continuity and shows the broad use of simulation as a computational tool to inform decision making processes. This edition also features expanded discussions of the analysis of variance, including single- and two-factor analyses, and a thorough treatment of Monte Carlo simulation. The authors not only clearly establish the limitations, advantages, and disadvantages of each method, but also show that data analysis is a continuum rather than the isolated application of different methods.

Like its predecessors, this book continues to serve its purpose well as both a textbook and a reference. Ultimately, readers will find the content of great value in problem solving and decision making, particularly in practical applications.

Preface

Chapter 1 : Introduction
Chapter 2 : Data Description and Treatment
Chapter 3 : Fundamentals of Probability
Chapter 4 : Probability Distributions for Discrete Random Variables
Chapter 5 : Probability Distributions for Continuous Random Variables
Chapter 6 : Multiple Random Variables
Chapter 7 : Simulation
Chapter 8 : Fundamentals of Statistical Analysis
Chapter 9 : Hypothesis Testing
Chapter 10 : Analysis of Variance
Chapter 11 : Confidence Intervals and Sample-Size Determination
Chapter 12 : Regression Analysis
Chapter 13 : Multiple and Nonlinear Regression Analysis
Chapter 14 : Reliability Analysis of Components
Chapter 15 : Reliability and Risk Analysis of Systems
Chapter 16 : Bayesian Methods

Appendix A : Probability and Statistics Tables
Appendix B : Taylor Series Expansion
Appendix C : Data for Simulation Projects
Appendix D : Semester Simulation Project
Index

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