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• Title Page
• Copyright Page
• Contents
• Preface
• Chapter 1 Introduction
• 1.1 Why Study Statistics?
• 1.2 Modern Statistics
• 1.3 Statistics and Engineering
• 1.4 The Role of the Scientist and Engineer in Quality Improvement
• 1.5 A Case Study: Visually Inspecting Data to Improve Product Quality
• 1.6 Two Basic Concepts—Population and Sample
• Review Exercises
• Key Terms
• Chapter 2 Organization and Description of Data
• 2.1 Pareto Diagrams and Dot Diagrams
• 2.2 Frequency Distributions
• 2.3 Graphs of Frequency Distributions
• 2.4 Stem-and-Leaf Displays
• 2.5 Descriptive Measures
• 2.6 Quartiles and Percentiles
• 2.7 The Calculation of x and s
• 2.8 A Case Study: Problems with Aggregating Data
• Review Exercises
• Key Terms
• Chapter 3 Probability
• 3.1 Sample Spaces and Events
• 3.2 Counting
• 3.3 Probability
• 3.4 The Axioms of Probability
• 3.5 Some Elementary Theorems
• 3.6 Conditional Probability
• 3.7 Bayes’ Theorem
• Review Exercises
• Key Terms
• Chapter 4 Probability Distributions
• 4.1 Random Variables
• 4.2 The Binomial Distribution
• 4.3 The Hypergeometric Distribution
• 4.4 The Mean and the Variance of a Probability Distribution
• 4.5 Chebyshev’s Theorem
• 4.6 The Poisson Distribution and Rare Events
• 4.7 Poisson Processes
• 4.8 The Geometric and Negative Binomial Distribution
• 4.9 The Multinomial Distribution
• 4.10 Simulation
• Review Exercises
• Key Terms
• Chapter 5 Probability Densities
• 5.1 Continuous Random Variables
• 5.2 The Normal Distribution
• 5.3 The Normal Approximation to the Binomial Distribution
• 5.4 Other Probability Densities
• 5.5 The Uniform Distribution
• 5.6 The Log-Normal Distribution
• 5.7 The Gamma Distribution
• 5.8 The Beta Distribution
• 5.9 TheWeibull Distribution
• 5.10 Joint Distributions—Discrete and Continuous
• 5.11 Moment Generating Functions
• 5.12 Checking If the Data Are Normal
• 5.13 Transforming Observations to Near Normality
• 5.14 Simulation
• Review Exercises
• Key Terms
• Chapter 6 Sampling Distributions
• 6.1 Populations and Samples
• 6.2 The Sampling Distribution of the Mean (σ known)
• 6.3 The Sampling Distribution of the Mean (σ unknown)
• 6.4 The Sampling Distribution of the Variance
• 6.5 Representations of the Normal Theory Distributions
• 6.6 The Moment Generating Function Method to Obtain Distributions
• 6.7 Transformation Methods to Obtain Distributions
• Review Exercises
• Key Terms
• Chapter 7 Inferences Concerning a Mean
• 7.1 Statistical Approaches to Making Generalizations
• 7.2 Point Estimation
• 7.3 Interval Estimation
• 7.4 Maximum Likelihood Estimation
• 7.5 Tests of Hypotheses
• 7.6 Null Hypotheses and Tests of Hypotheses
• 7.7 Hypotheses Concerning One Mean
• 7.8 The Relation between Tests and Confidence Intervals
• 7.9 Power, Sample Size, and Operating Characteristic Curves
• Review Exercises
• Key Terms
• Chapter 8 Comparing Two Treatments
• 8.1 Experimental Designs for Comparing Two Treatments
• 8.2 Comparisons—Two Independent Large Samples
• 8.3 Comparisons—Two Independent Small Samples
• 8.4 Matched Pairs Comparisons
• 8.5 Design Issues—Randomization and Pairing
• Review Exercises
• Key Terms
• Chapter 9 Inferences Concerning Variances
• 9.1 The Estimation of Variances
• 9.2 Hypotheses Concerning One Variance
• 9.3 Hypotheses Concerning Two Variances
• Review Exercises
• Key Terms
• Chapter 10 Inferences Concerning Proportions
• 10.1 Estimation of Proportions
• 10.2 Hypotheses Concerning One Proportion
• 10.3 Hypotheses Concerning Several Proportions
• 10.4 Analysis of r x c Tables
• 10.5 Goodness of Fit
• Review Exercises
• Key Terms
• Chapter 11 Regression Analysis
• 11.1 The Method of Least Squares
• 11.2 Inferences Based on the Least Squares Estimators
• 11.3 Curvilinear Regression
• 11.4 Multiple Regression
• 11.5 Checking the Adequacy of the Model
• 11.6 Correlation
• 11.7 Multiple Linear Regression (Matrix Notation)
• Review Exercises
• Key Terms
• Chapter 12 Analysis of Variance
• 12.1 Some General Principles
• 12.2 Completely Randomized Designs
• 12.3 Randomized-Block Designs
• 12.4 Multiple Comparisons
• 12.5 Analysis of Covariance
• Review Exercises
• Key Terms
• Chapter 13 Factorial Experimentation
• 13.1 Two-Factor Experiments
• 13.2 Multifactor Experiments
• 13.3 The Graphic Presentation of 22 and 23 Experiments
• 13.4 Response Surface Analysis
• Review Exercises
• Key Terms
• Chapter 14 Nonparametric Tests
• 14.1 Introduction
• 14.2 The Sign Test
• 14.3 Rank-Sum Tests
• 14.4 Correlation Based on Ranks
• 14.5 Tests of Randomness
• 14.6 The Kolmogorov-Smirnov and Anderson-Darling Tests
• Review Exercises
• Key Terms
• Chapter 15 The Statistical Content of Quality-Improvement Programs
• 15.1 Quality-Improvement Programs
• 15.2 Starting a Quality-Improvement Program
• 15.3 Experimental Designs for Quality
• 15.4 Quality Control
• 15.5 Control Charts for Measurements
• 15.6 Control Charts for Attributes
• 15.7 Tolerance Limits
• Review Exercises
• Key Terms
• Chapter 16 Application to Reliability and Life Testing
• 16.1 Reliability
• 16.2 Failure-Time Distribution
• 16.3 The Exponential Model in Life Testing
• 16.4 The Weibull Model in Life Testing
• Review Exercises
• Key Terms
• Appendix A Bibliography
• Appendix B Statistical Tables
• Appendix C Using the R Software Program
• Introduction to R
• Entering Data
• Arithmetic Operations
• Descriptive Statistics
• Probability Distributions
• Normal Probability Calculations
• Sampling Distributions
• Confidence Intervals and Tests of Means
• Inference about Proportions
• Regression
• One-Way Analysis of Variance (ANOVA)
• Appendix D Answers to Odd-Numbered Exercises
• Index
• A
• B
• C
• D
• E
• F
• G
• H
• I
• J
• K
• L
• M
• N
• O
• P
• Q
• R
• S
• T
• U
• V
• W
• X
• Z