Table of ContentsPART I: PRINCIPLES OF STATISTICAL THINKING AND ANALYSIS 1. THE ROLE OF STATISTICAL METHODS IN MODERN INDUSTRY The Different Functional Areas in Industry / The Quality-Productivity Dilemma / Fire Fighting / Inspection of Products / Process Control / Quality by Design / Chapter Summary / Exercises 2. UNDERSTANDING VARIABILITY Random Phenomena and the Structure of Observations / Accuracy and Precision of Measurements / The Population and the Sample / Descriptive Analysis of Sample Data / Prediction Intervals / Additional Techniques of Exploratory Data Analysis / Chapter Summary / Exercises 3. VARIABILITY IN SEVERAL DIMENSIONS Graphical Display and Analysis / Dynamic Graphics / Frequency Distributions in Several Dimensions / Correlation and Regression Analysis / Contingency Tables / Chapter Summary / Exercises 4. BASIC MODELS OF PROBABILITY AND DISTRIBUTION FUNCTIONS Basic Probability / Random Variables and Their Distributions / Families of Discrete Distributions / Continuous Distributions / Joint, Marginal, and Conditional Distributions / Some Multivariate Distributions / Distribution of Order Statistics / Linear Combination of Random Variables / Large Sample Approximations / Additional Distributions of Statistics of Normal Samples / Chapter Summary / Exercises 5. SAMPLING FOR ESTIMATION OF FINITE POPULATION QUANTITIES Sampling and the Estimation Problem / Estimating with Simple Random Samples / Estimating the Mean with Stratified RSWOR / Proportional and Optimal Allocation / Prediction Models with Known Covariates / Chapter Summary / Exercises 6. PARAMETRIC STATISTICAL INFERENCE Sampling Characteristics of Estimator / Methods of Point Estimation / Confidence Intervals / Tolerance Intervals / Comparison of Sample Estimates with Specified Standards-Testing / Testing for Normality with Probability Plots / Tests of Goodness of Fit / Bayesian Decision Procedures / Chapter Summary / Exercises 7. DISTRIBUTION-FREE INFERENCE: COMPUTER INTENSIVE TECHNIQUES Random Sampling from Reference Distributions / Bootstrap Sampling / Bootstrap Testing of Hypotheses / Bootstrap Tolerance Intervals / Non-Parametric Tests / Description of MINITAB Macros and Executable Files used in Chapter 7 / Chapter Summary / Exercises 8. MULTIPLE LINEAR REGRESSION AND ANALYSIS OF VARIANCE Regression on Two Variables / Partial Regression and Correlation / Multiple Linear Regression / Partial F-Tests and the Sequential SS / Model Construction: Step-Wise Regression / Regression Diagnostics / Chapter Summary / Exercises PART II: METHODS OF INDUSTRIAL STATISTICS 9. SAMPLING PLANS FOR PRODUCT INSPECTION General Discussion / Single-Stage Sampling Plans for Attributes / Approximate Determination of the Sampling Plan / Double-Sampling Plans for Attributes / Sequential Sampling / Acceptance Sampling Plans for Variables / Rectifying Inspection of Lots / National and International Standards / Skip Lot Sampling for Attributes / The Deming Inspection Criterion / Published Tables for Acceptance Sampling / Chapter Summary / Exercises 10. BASIC TOOLS AND PRINCIPLES OF STATISTICAL PROCESS CONTROL Basic Concepts of Statistical Process Control / Driving a Process with Control Charts / Setting Up a Control Chart: Process Capability Studies / Process Capability Indices / Seven Tools for Process Control and Process Improvement / Statistical Analysis of Pareto Charts / The Shewhart Control Charts / Chapter Summary / Exercises 11. ADVANCED METHODS OF STATISTICAL PROCESS CONTROL Tests of Randomness / Modified Shewhart Control Charts for Chi / The Size and Frequency of Sampling for Shewhart Control Charts / Multivariate Control Charts / Cumulative Sum Control Charts / Bayesian Detection / Process Tracking / Automatic Process Control / Chapter Summary / Exercises 12. CLASSICAL DESIGN AND ANALYSIS OF EXPERIMENTS Basic Steps and Guiding Principles / Blocking and Randomization / Additive and Non-Additive Linear Models: Main Effects and Interactions / The Analysis of Randomized Comple