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Applied Statistics and Probability for Engineers, 5th Edition

Name: Applied Statistics and Probability for Engineers, 5th Edition
ISBN: 9780470053041

by George C. Runger, Douglas C. Montgomery

March 2010

Intermediate to advanced

784 pages

31h 22m

English

Wiley

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Coverpage
Titlepage
Copyright
Contents
Preface
INSIDE FRONT COVER Index of Applications in Examples and Exercises
CHAPTER 1 The Role of Statistics in Engineering
1-1 The Engineering Method and Statistical Thinking1-2 Collecting Engineering Data1-2.1 Basic Principles1-2.2 Retrospective Study1-2.3 Observational Study1-2.4 Designed Experiments1-2.5 Observing Processes Over Time1-3 Mechanistic and Empirical Models1-4 Probability and Probability Models
CHAPTER 2 Probability
2-1 Sample Spaces and Events2-1.1 Random Experiments2-1.2 Sample Spaces2-1.3 Events2-1.4 Counting Techniques2-2 Interpretations and Axioms of Probability2-3 Addition Rules2-4 Conditional Probability2-5 Multiplication and Total Probability Rules2-6 Independence2-7 Bayes’ Theorem2-8 Random Variables
CHAPTER 3 Discrete Random Variables and Probability Distributions
3-1 Discrete Random Variables3-2 Probability Distributions and Probability Mass Functions3-3 Cumulative Distribution Functions3-4 Mean and Variance of a Discrete Random Variable3-5 Discrete Uniform Distribution3-6 Binomial Distribution3-7 Geometric and Negative Binomial Distributions3-8 Hypergeometric Distribution3-9 Poisson Distribution
CHAPTER 4 Continuous Random Variables and Probability Distributions
4-1 Continuous Random Variables4-2 Probability Distributions and Probability Density Functions4-3 Cumulative Distribution Functions4-4 Mean and Variance of a Continuous Random Variable4-5 Continuous Uniform Distribution4-6 Normal Distribution4-7 Normal Approximation to the Binomial and Poisson Distributions4-8 Exponential Distribution4-9 Erlang and Gamma Distributions4-10 Weibull Distribution4-11 Lognormal Distribution4-12 Beta Distribution

CHAPTER 5 Joint Probability Distributions
5-1 Two or More Random Variables5-1.1 Joint Probability Distributions5-1.2 Marginal Probability Distributions5-1.3 Conditional Probability Distributions5-1.4 Independence5-1.5 More Than Two Random Variables5-2 Covariance and Correlation5-3 Common Joint Distributions5-3.1 Multinomial Distribution5-3.2 Bivariate Normal Distribution5-4 Linear Functions of Random Variables5-5 General Functions of Random Variables
CHAPTER 6 Descriptive Statistics
6-1 Numerical Summaries of Data6-2 Stem-and-Leaf Diagrams6-3 Frequency Distributions and Histograms6-4 Box Plots6-5 Time Sequence Plots6-6 Probability Plots
CHAPTER 7 Sampling Distributions and Point Estimation of Parameters
7-1 Point Estimation7-2 Sampling Distributions and the Central Limit Theorem7-3 General Concepts of Point Estimation7-3.1 Unbiased Estimators7-3.2 Variance of a Point Estimator7-3.3 Standard Error: Reporting a Point Estimate7-3.4 Mean Squared Error of an Estimator7-4 Methods of Point Estimation7-4.1 Method of Moments7-4.2 Method of Maximum Likelihood7-4.3 Bayesian Estimation of Parameters
CHAPTER 8 Statistical Intervals for a Single Sample
8-1 Confidence Interval on the Mean of a Normal Distribution, Variance Known8-1.1 Development of the Confidence Interval and Its Basic Properties8-1.2 Choice of Sample Size8-1.3 One-sided Confidence Bounds8-1.4 General Method to Derive a Confidence Interval8-1.5 Large-Sample Confidence Interval for μ8-2 Confidence Interval on the Mean of a Normal Distribution, Variance Unknown8-2.1 t Distribution8-2.2 t Confidence Interval on μ8-3 Confidence Interval on the Variance and Standard Deviation of a Normal Distribution8-4 Large-Sample Confidence Interval for a Population Proportion8-5 Guidelines for Constructing Confidence Intervals8-6 Tolerance and Prediction Intervals8-6.1 Prediction Interval for a Future Observation8-6.2 Tolerance Interval for a Normal Distribution
CHAPTER 9 Tests of Hypotheses for a Single Sample
9-1 Hypothesis Testing9-1.1 Statistical Hypotheses9-1.2 Tests of Statistical Hypotheses9-1.3 One-Sided and Two-Sided Hypothesis9-1.4 P-Values in Hypothesis Tests9-1.5 Connection between Hypothesis Tests and Confidence Intervals9-1.6 General Procedure for Hypothesis Tests9-2 Tests on the Mean of a Normal Distribution, Variance Known9-2.1 Hypothesis Tests on the Mean9-2.2 Type II Error and Choice of Sample Size9-2.3 Large-Sample Test9-3 Tests on the Mean of a Normal Distribution, Variance Unknown9-3.1 Hypothesis Tests on the Mean9-3.2 Type II Error and Choice of Sample Size9-4 Tests on the Variance and Standard Deviation of a Normal Distribution9-4.1 Hypothesis Tests on the Variance9-4.2 Type II Error and Choice of Sample Size9-5 Tests on a Population Proportion9-5.1 Large-Sample Tests on a Proportion9-5.2 Type II Error and Choice of Sample Size9-6 Summary Table of Inference Procedures for a Single Sample9-7 Testing for Goodness of Fit9-8 Contingency Table Tests9-9 Nonparametric Procedures9-9.1 The Sign Test9-9.2 The Wilcoxon Signed-Rank Test9-9.3 Comparison to the t-Test
CHAPTER 10 Statistical Inference for Two Samples
10-1 Inference on the Difference in Means of Two Normal Distributions, Variances Known10-1.1 Hypothesis Tests on the Difference in Means, Variances Known10-1.2 Type II Error and Choice of Sample Size10-1.3 Confidence Interval on the Difference in Means, Variances Known10-2 Inference on the Difference in Means of Two Normal Distributions, Variances Unknown10-2.1 Hypothesis Tests on the Difference in Means, Variances Unknown10-2.2 Type II Error and Choice of Sample Size10-2.3 Confidence Interval on the Difference in Means, Variances Unknown10-3 A Nonparametric Test for the Difference in Two Means10-3.1 Description of the Wilcoxon Rank-Sum Test10-3.2 Large-Sample Approximation10-3.3 Comparison to the t-Test10-4 Paired t-Test10-5 Inference on the Variances of Two Normal Distributions10-5.1 F Distribution10-5.2 Hypothesis Tests on the Ratio of Two Variances10-5.3 Type II Error and Choice of Sample Size10-5.4 Confidence Interval on the Ratio of Two Variances10-6 Inference on Two Population Proportions10-6.1 Large-Sample Tests on the Difference in Population Proportions10-6.2 Type II Error and Choice of Sample Size10-6.3 Confidence Interval on the Difference in Population Proportions10-7 Summary Table and Roadmap for Inference Procedures for Two Samples
CHAPTER 11 Simple Linear Regression and Correlation
11-1 Empirical Models11-2 Simple Linear Regression11-3 Properties of the Least Squares Estimators11-4 Hypothesis Tests in Simple Linear Regression11-4.1 Use of t-Tests11-4.2 Analysis of Variance Approach to Test Significance of Regression11-5 Confidence Intervals11-5.1 Confidence Intervals on the Slope and Intercept11-5.2 Confidence Interval on the Mean Response11-6 Prediction of New Observations11-7 Adequacy of the Regression Model11-7.1 Residual Analysis11-7.2 Coefficient of Determination (R2)11-8 Correlation11-9 Regression on Transformed Variables11-10 Logistic Regression
CHAPTER 12 Multiple Linear Regression
12-1 Multiple Linear Regression Model12-1.1 Introduction12-1.2 Least Squares Estimation of the Parameters12-1.3 Matrix Approach to Multiple Linear Regression12-1.4 Properties of the Least Squares Estimators12-2 Hypothesis Tests in Multiple Linear Regression12-2.1 Test for Significance of Regression12-2.2 Tests on Individual Regression Coefficients and Subsets of Coefficients12-3 Confidence Intervals in Multiple Linear Regression12-3.1 Confidence Intervals on Individual Regression Coefficients12-3.2 Confidence Interval on the Mean Response12-4 Prediction of New Observations12-5 Model Adequacy Checking12-5.1 Residual Analysis12-5.2 Influential Observations12-6 Aspects of Multiple Regression Modeling12-6.1 Polynomial Regression Models12-6.2 Categorical Regressors and Indicator Variables12-6.3 Selection of Variables and Model Building12-6.4 Multicollinearity
CHAPTER 13 Design and Analysis of Single-Factor Experiments: The Analysis of Variance
13-1 Designing Engineering Experiments13-2 Completely Randomized Single-Factor Experiment13-2.1 Example: Tensile Strength13-2.2 Analysis of Variance13-2.3 Multiple Comparisons Following the ANOVA13-2.4 Residual Analysis and Model Checking13-2.5 Determining Sample Size13-3 The Random-Effects Model13-3.1 Fixed Versus Random Factors13-3.2 ANOVA and Variance Components13-4 Randomized Complete Block Design13-4.1 Design and Statistical Analysis13-4.2 Multiple Comparisons13-4.3 Residual Analysis and Model Checking
CHAPTER 14 Design of Experiments with Several Factors
14-1 Introduction14-2 Factorial Experiments14-3 Two-Factor Factorial Experiments14-3.1 Statistical Analysis of the Fixed-Effects Model14-3.2 Model Adequacy Checking14-3.3 One Observation per Cell14-4 General Factorial Experiments14-5 2k Factorial Designs14-5.1 22 Design14-5.2 2k Design for k ≥ 3 Factors14-5.3 Single Replicate of the 2k Design14-5.4 Addition of Center Points to a 2k Design14-6 Blocking and Confounding in the 2k Design14-7 Fractional Replication of the 2k Design14-7.1 One-Half Fraction of the 2k Design14-7.2 Smaller Fractions: The 2k−p Fractional Factorial14-8 Response Surface Methods and Designs
CHAPTER 15 Statistical Quality Control
15-1 Quality Improvement and Statistics15-1.1 Statistical Quality Control15-1.2 Statistical Process Control15-2 Introduction to Control Charts15-2.1 Basic Principles15-2.2 Design of a Control Chart15-2.3 Rational Subgroups15-2.4 Analysis of Patterns on Control Charts15-3 X and R or S Control Charts15-4 Control Charts for Individual Measurements15-5 Process Capability15-6 Attribute Control Charts15-6.1 P Chart (Control Chart for Proportions)15-6.2 U Chart (Control Chart for Defects per Unit)15-7 Control Chart Performance15-8 Time-Weighted Charts15-8.1 Cumulative Sum Control Chart15-8.2 Exponentially Weighted Moving Average Control Chart15-9 Other SPC Problem-Solving Tools15-10 Implementing SPC
APPENDICES
APPENDIX A: Statistical Tables and ChartsTable I Summary of Common Probability DistributionsTable II Cumulative Binomial Probability P(X ≤ x)Table III Cumulative Standard Normal DistributionTable IV Percentage Points χ2α, v of the Chi-Squared DistributionTable V Percentage Points tα, v of the t distributionTable VI Percentage Points fα, v1,v2 of the F distributionChart VII Operating Characteristic CurvesTable VIII Critical Values for the Sign TestTable IX Critical Values for the Wilcoxon Signed-Rank TestTable X Critical Values for the Wilcoxon Rank-Sum TestTable XI Factors for Constructing Variables Control ChartsTable XII Factors for Tolerance Intervals
APPENDIX B: Answers to Selected Exercises
APPENDIX C: Bibliography
GLOSSARY
INDEX
INDEX OF APPLICATIONS IN EXAMPLES AND EXERCISES, CONTINUED

Content preview from Applied Statistics and Probability for Engineers, 5th Edition

APPENDICES

APPENDIX A. STATISTICAL TABLES AND CHARTS

Table I	Summary of Common Probability Distributions
Table II	Cumulative Binomial Probabilities P(X ≤ x)
Table III	Cumulative Standard Normal Distribution
Table IV	Percentage Points χ²_α,ν of the Chi-Squared Distribution
Table V	Percentage Points t_α,ν of the t Distribution
Table VI	Percentage Points f_{α, ν₁, ν₂} of the F Distribution
Chart VII	Operating Characteristic Curves
Table VIII	Critical Values for the Sign Test
Table IX	Critical Values for the Wilcoxon Signed-Rank Test
Table X	Critical Values for the Wilcoxon Rank-Sum Test
Table XI	Factors for Constructing Variables Control Charts
Table XII	Factors for Tolerance Intervals

APPENDIX B. ANSWERS TO SELECTED EXERCISE

APPENDIX C. BIBLIOGRAPHY

Appendix A

Statistical Tables and Charts

Table I Summary of Common Probability Distributions

images

Table II Cumulative Binomial Probabilities P(X ≤ x)

images

Table III Cumulative Standard Normal Distribution

Table IV ...

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