Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition

by Ayyub; Bilal M.

• ISBN13: 9781584882862
• ISBN10: 1584882867
• Additional ISBN(s): 9780849326905
• Edition: 2nd
• Format: Hardcover
• Copyright: 2002-06-26
• Publisher: Chapman & Hall/
• More Book Details
• Purchase Benefits

Summary

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.The second edition of this bestselling text introduces 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. It 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 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.Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition, was designed as both a reference and as a textbook, and it serves each purpose well. Ultimately, readers will find its content of great value in problem solving and decision making, particularly in practical applications.

Author Biography

Richard H. McCuen is a Professor of Civil and Environmental Engineering at the University of Maryland, College Park, USA.

Table of Contents

INTRODUCTION

Types of Uncertainty

Introduction to Simulation

DATA DESCRIPTION AND TREATMENT

Classification of Data

Graphical Description of Data

Histograms and Frequency Diagrams

Descriptive Measures

Applications

Analysis of Simulated Data

FUNDAMENTALS OF PROBABILITY

Sample Spaces, Sets, and Events

Mathematics of Probability

Random Variables and their Probability Distributions

Moments

Application: Water Supply and Quality

Simulation and Probability Distributions

PROBABILITY DISTRIBUTIONS FOR DISCRETE RANDOM VARIABLES

Bernoulli Distribution

Binomial Distribution

Geometric Distribution

Poisson Distribution

Negative Binomial and Pascal Probability Distributions

Hypergeometric Probability Distribution

Applications.

Simulation of Discrete Random Variables

PROBABILITY DISTRIBUTIONS FOR CONTINUOUS RANDOM VARIABLES

Uniform Distribution

Normal Distribution

Lognormal Distribution

Exponential Distribution

Triangular Distribution

Gamma Distribution

Rayleigh Distribution

Statistical Probability Distributions

Extreme Value Distributions

Applications

Simulation and Probability Distributions

MULTIPLE RANDOM VARIABLES

Joint Random Variables and their Probability Distributions

Functions of Random Variables

Applications

Multivariable Simulation

SIMULATION

Monte Carlo Simulation

Random Numbers

Generation of Random Variables

Generation of Selected Discrete Random Variables

Generation of Selected Continuous Random Variables

Applications

FUNDAMENTALS OF STATISTICAL ANALYSIS

Estimation of Parameters

Sampling Distributions

Applications

HYPOTHESIS TESTING

General Procedure

Hypothesis Tests of Means

Hypothesis Tests of Variances

Tests of Distributions

Applications

Simulation of Hypothesis Test Assumptions

ANALYSIS OF VARIANCE

Test of Population Means

Multiple Comparisons in the ANOVA Test

Test of Population Variances

Randomized Block Design

Two-Way Analysis of Variance

Applications

CONFIDENCE INTERVALS AND SAMPLE SIZE DETERMINATION

General Procedure

Confidence Intervals on Sample Statistics

Sample-Size Determination

Applications

REGRESSION ANALYSIS

Correlation Analysis

Introduction to Regression

Principle of Least Squares

Reliability of the Regression Equation

Reliability of Point Estimates of the Regression Coefficients

Confidence Intervals of the Regression Equation

Correlation vs. Regression

Applications of Bivariate Regression Analysis

Simulation and Prediction Models

MULTIPLE AND NONLINEAR REGRESSION ANALYSIS

Correlation Analysis

Multiple Regression Analysis

Polynomial Regression Analysis

Regression Analysis of Power Models

Applications.

Simulation in Curvilinear Modeling

RELIABILITY ANALYSIS OF COMPONENTS

Time to Failure

Reliability of Components

First-Order Reliability Method

Advanced Second-Moment Method

Simulation Methods

Reliability-Based Design

Application: Structural Reliability of a Pressure Vessel

RELIABILITY AND RISK ANALYSIS OF SYSTEMS

Reliability of Systems

Risk Analysis

Risk-Based Decision Analysis

Application: System Reliability of a Post-Tensioned Truss

BAYESIAN METHODS

Bayesian Probabilities

Bayesian Estimation of Parameters

Bayesian Statistics

Applications

Appendix A: Probability and Statistics Tables

Appendix B: Taylor Series Expansion

Appendix C: Data for Simulation Projects.

Index

Each chapter also contains an Introduction, Problems, and Simulation Projects.