Engineering Statistics, 5th Edition
December 2010, ©2011
1-1 The Engineering Method and Statistical Thinking.
1-2 Collecting Engineering Data.
1-3 Mechanistic and Empirical Models.
1-4 Observing Processes Over Time.
CHAPTER 2 Data Summary and Presentation.
2-1 Data Summary and Display.
2-2 Stem-and-Leaf Diagram.
2-4 Box Plot.
2-5 Time Series Plots.
2-6 Multivariate Data.
CHAPTER 3 Random Variables and Probability Distributions.
3-2 Random Variables.
3-4 Continuous Random Variables.
3-5 Important Continuous Distributions.
3-6 Probability Plots.
3-7 Discrete Random Variables.
3-8 Binomial Distribution.
3-9 Poisson Process.
3-10 Normal Approximation to the Binomial and Poisson Distributions.
3-11 More than One Random Variable and Independence.
3-12 Functions of Random Variables.
3-13 Random Samples, Statistics, and the Central Limit Theorem.
CHAPTER 4 Decision Making for a Single Sample.
4-1 Statistical Inference.
4-2 Point Estimation.
4-3 Hypothesis Testing.
4-4 Inference on the Mean of a Population, Variance Known.
4-5 Inference on the Mean of a Population, Variance Unknown.
4-6 Inference on the Variance of a Normal Population.
4-7 Inference on a Population Proportion.
4-8 Other Interval Estimates for a Single Sample.
4-9 Summary Tables of Inference Procedures for a Single Sample.
4-10 Testing for Goodness of Fit.
CHAPTER 5 Decision Making for Two Samples.
5-2 Inference on the Means of Two Populations, Variances Known.
5-3 Inference on the Means of Two Populations, Variances Unknown.
5-4 The Paired t-Test.
5-5 Inference on the Ratio of Variances of Two Normal Populations.
5-6 Inference on Two Population Proportions.
5-7 Summary Tables for Inference Procedures for Two Samples.
5-8 What if We Have More than Two Samples?
CHAPTER 6 Building Empirical Models.
6-1 Introduction to Empirical Models.
6-2 Simple Linear Regression.
6-3 Multiple Regression.
6-4 Other Aspects of Regression.
CHAPTER 7 Design of Engineering Experiments.
7-1 The Strategy of Experimentation.
7-2 Factorial Experiments.
7-3 2k Factorial Design.
7-4 Center Points and Blocking in 2k Designs.
7-5 Fractional Replication of a 2k Design.
7-6 Response Surface Methods and Designs.
7-7 Factorial Experiments With More Than Two Levels.
CHAPTER 8 Statistical Process Control.
8-1 Quality Improvement and Statistical Process Control.
8-2 Introduction to Control Charts.
8-3 X and R Control Charts.
8-4 Control Charts For Individual Measurements.
8-5 Process Capability.
8-6 Attribute Control Charts.
8-7 Control Chart Performance.
8-8 Measurement Systems Capability.
APPENDIX A Statistical Tables and Charts.
APPENDIX B Bibliography.
APPENDIX C Answers to Selected Exercises.
- 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 P-value 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 step-by-step 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 in-class 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