Textbook
Engineering Statistics, 5th EditionDecember 2010, ©2011

11 The Engineering Method and Statistical Thinking.
12 Collecting Engineering Data.
13 Mechanistic and Empirical Models.
14 Observing Processes Over Time.
CHAPTER 2 Data Summary and Presentation.
21 Data Summary and Display.
22 StemandLeaf Diagram.
23 Histograms.
24 Box Plot.
25 Time Series Plots.
26 Multivariate Data.
CHAPTER 3 Random Variables and Probability Distributions.
31 Introduction.
32 Random Variables.
33 Probability.
34 Continuous Random Variables.
35 Important Continuous Distributions.
36 Probability Plots.
37 Discrete Random Variables.
38 Binomial Distribution.
39 Poisson Process.
310 Normal Approximation to the Binomial and Poisson Distributions.
311 More than One Random Variable and Independence.
312 Functions of Random Variables.
313 Random Samples, Statistics, and the Central Limit Theorem.
CHAPTER 4 Decision Making for a Single Sample.
41 Statistical Inference.
42 Point Estimation.
43 Hypothesis Testing.
44 Inference on the Mean of a Population, Variance Known.
45 Inference on the Mean of a Population, Variance Unknown.
46 Inference on the Variance of a Normal Population.
47 Inference on a Population Proportion.
48 Other Interval Estimates for a Single Sample.
49 Summary Tables of Inference Procedures for a Single Sample.
410 Testing for Goodness of Fit.
CHAPTER 5 Decision Making for Two Samples.
51 Introduction.
52 Inference on the Means of Two Populations, Variances Known.
53 Inference on the Means of Two Populations, Variances Unknown.
54 The Paired tTest.
55 Inference on the Ratio of Variances of Two Normal Populations.
56 Inference on Two Population Proportions.
57 Summary Tables for Inference Procedures for Two Samples.
58 What if We Have More than Two Samples?
CHAPTER 6 Building Empirical Models.
61 Introduction to Empirical Models.
62 Simple Linear Regression.
63 Multiple Regression.
64 Other Aspects of Regression.
CHAPTER 7 Design of Engineering Experiments.
71 The Strategy of Experimentation.
72 Factorial Experiments.
73 2^{k} Factorial Design.
74 Center Points and Blocking in 2^{k} Designs.
75 Fractional Replication of a 2^{k} Design.
76 Response Surface Methods and Designs.
77 Factorial Experiments With More Than Two Levels.
CHAPTER 8 Statistical Process Control.
81 Quality Improvement and Statistical Process Control.
82 Introduction to Control Charts.
83 X and R Control Charts.
84 Control Charts For Individual Measurements.
85 Process Capability.
86 Attribute Control Charts.
87 Control Chart Performance.
88 Measurement Systems Capability.
APPENDICES.
APPENDIX A Statistical Tables and Charts.
APPENDIX B Bibliography.
APPENDIX C Answers to Selected Exercises.
INDEX.
 New introductions in each chapter demonstrate the relevance of statistics to engineering
 Design of experiments content revised and inclusion of additional material helps students to better interpret computer software output related to ANOVA
 New examples demonstrate calculating probability in Excel (Chapter 3)
 Practical interpretations in example problems provide improved linking of statistical conclusions to the actual engineering decision outcome
 Approximately 80 new exercises related to biology and health care (in most chapters)
 Accessible and manageable  presents important topics that can be covered in one semester
 Emphasis on professional practice  students get the coverage most useful to engineers with strong emphasis on data analysis and statistical inference with less focus on distributions and probability
 A strong focus on Pvalue approach to hypothesis testing familiarizes students with practical approaches to engineering problems
 Provides real engineering situations and applications as well as real data sets in examples and homework that help motivate students by applying statistics to the engineering profession
 A stepbystep problem solving approach integrated into examples
 Supports an active learning environment  reading questions and homework problems in WileyPlus help motivate and build student confidence with instant feedback. The supplemental problems and team exercises in the text can be used for inclass team activities, including designing experiments, generating data, and performing analyses.
 End of section exercises are structured to reinforce the concepts and technigues introduced in each section
 End of chapter supplemental exercises integrate concepts and techniques from multiple sections and reinforce student mastery of these concepts
 Team exercises challenge students to apply chapter methods and concepts to problems requiring data collection
 Software output in MINITAB throughout the text demonstrates the capability of modern statistical software
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