Book description
Montgomery and Runger's bestselling engineering statistics text provides a practical approach oriented to engineering as well as chemical and physical sciences. By providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers and is suitable for a one or twoterm course in probability and statistics.
With a focus on how statistical tools are integrated into the engineering problemsolving process, all major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples, building regression models, designing and analyzing engineering experiments, and statistical process control.
Developed with sponsorship from the National Science Foundation, this text incorporates many insights from the authors' teaching experience along with feedback from numerous adopters of previous editions.
Table of contents
 Coverpage
 Titlepage
 Copyright
 Contents
 Preface
 INSIDE FRONT COVER Index of Applications in Examples and Exercises
 CHAPTER 1 The Role of Statistics in Engineering
 CHAPTER 2 Probability

CHAPTER 3 Discrete Random Variables and Probability Distributions
 31 Discrete Random Variables
 32 Probability Distributions and Probability Mass Functions
 33 Cumulative Distribution Functions
 34 Mean and Variance of a Discrete Random Variable
 35 Discrete Uniform Distribution
 36 Binomial Distribution
 37 Geometric and Negative Binomial Distributions
 38 Hypergeometric Distribution
 39 Poisson Distribution

CHAPTER 4 Continuous Random Variables and Probability Distributions
 41 Continuous Random Variables
 42 Probability Distributions and Probability Density Functions
 43 Cumulative Distribution Functions
 44 Mean and Variance of a Continuous Random Variable
 45 Continuous Uniform Distribution
 46 Normal Distribution
 47 Normal Approximation to the Binomial and Poisson Distributions
 48 Exponential Distribution
 49 Erlang and Gamma Distributions
 410 Weibull Distribution
 411 Lognormal Distribution
 412 Beta Distribution
 CHAPTER 5 Joint Probability Distributions
 CHAPTER 6 Descriptive Statistics
 CHAPTER 7 Sampling Distributions and Point Estimation of Parameters

CHAPTER 8 Statistical Intervals for a Single Sample
 81 Confidence Interval on the Mean of a Normal Distribution, Variance Known
 82 Confidence Interval on the Mean of a Normal Distribution, Variance Unknown
 83 Confidence Interval on the Variance and Standard Deviation of a Normal Distribution
 84 LargeSample Confidence Interval for a Population Proportion
 85 Guidelines for Constructing Confidence Intervals
 86 Tolerance and Prediction Intervals

CHAPTER 9 Tests of Hypotheses for a Single Sample
 91 Hypothesis Testing
 92 Tests on the Mean of a Normal Distribution, Variance Known
 93 Tests on the Mean of a Normal Distribution, Variance Unknown
 94 Tests on the Variance and Standard Deviation of a Normal Distribution
 95 Tests on a Population Proportion
 96 Summary Table of Inference Procedures for a Single Sample
 97 Testing for Goodness of Fit
 98 Contingency Table Tests
 99 Nonparametric Procedures

CHAPTER 10 Statistical Inference for Two Samples
 101 Inference on the Difference in Means of Two Normal Distributions, Variances Known
 102 Inference on the Difference in Means of Two Normal Distributions, Variances Unknown
 103 A Nonparametric Test for the Difference in Two Means
 104 Paired tTest
 105 Inference on the Variances of Two Normal Distributions
 106 Inference on Two Population Proportions
 107 Summary Table and Roadmap for Inference Procedures for Two Samples

CHAPTER 11 Simple Linear Regression and Correlation
 111 Empirical Models
 112 Simple Linear Regression
 113 Properties of the Least Squares Estimators
 114 Hypothesis Tests in Simple Linear Regression
 115 Confidence Intervals
 116 Prediction of New Observations
 117 Adequacy of the Regression Model
 118 Correlation
 119 Regression on Transformed Variables
 1110 Logistic Regression
 CHAPTER 12 Multiple Linear Regression
 CHAPTER 13 Design and Analysis of SingleFactor Experiments: The Analysis of Variance
 CHAPTER 14 Design of Experiments with Several Factors

CHAPTER 15 Statistical Quality Control
 151 Quality Improvement and Statistics
 152 Introduction to Control Charts
 153 X and R or S Control Charts
 154 Control Charts for Individual Measurements
 155 Process Capability
 156 Attribute Control Charts
 157 Control Chart Performance
 158 TimeWeighted Charts
 159 Other SPC ProblemSolving Tools
 1510 Implementing SPC

APPENDICES

APPENDIX A: Statistical Tables and Charts
 Table I Summary of Common Probability Distributions
 Table II Cumulative Binomial Probability P(X ≤ x)
 Table III Cumulative Standard Normal Distribution
 Table IV Percentage Points χ2α, v of the ChiSquared Distribution
 Table V Percentage Points tα, v of the t distribution
 Table VI Percentage Points fα, v1,v2 of the F distribution
 Chart VII Operating Characteristic Curves
 Table VIII Critical Values for the Sign Test
 Table IX Critical Values for the Wilcoxon SignedRank Test
 Table X Critical Values for the Wilcoxon RankSum Test
 Table XI Factors for Constructing Variables Control Charts
 Table XII Factors for Tolerance Intervals
 APPENDIX B: Answers to Selected Exercises
 APPENDIX C: Bibliography

APPENDIX A: Statistical Tables and Charts
 GLOSSARY
 INDEX
 INDEX OF APPLICATIONS IN EXAMPLES AND EXERCISES, CONTINUED
Product information
 Title: Applied Statistics and Probability for Engineers, 5th Edition
 Author(s):
 Release date: March 2010
 Publisher(s): Wiley
 ISBN: 9780470053041
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