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• Title Page
• Copyright Page
• Dedication
• Contents
• Preface
• Acknowledgments
• Acknowledgments for the Global Edition
• 1 Introduction to Statistics and Data Analysis
• 1.1 Overview: Statistical Inference, Samples, Populations, and the Role of Probability
• 1.2 Sampling Procedures; Collection of Data
• 1.3 Measures of Location: The Sample Mean and Median
• Exercises
• 1.4 Measures of Variability
• Exercises
• 1.5 Discrete and Continuous Data
• 1.6 Statistical Modeling, Scientific Inspection, and Graphical Diagnostics
• 1.7 General Types of Statistical Studies: Designed Experiment, Observational Study, and Retrospectiv
• Exercises
• 2 Probability
• 2.1 Sample Space
• 2.2 Events
• Exercises
• 2.3 Counting Sample Points
• Exercises
• 2.4 Probability of an Event
• 2.5 Additive Rules
• Exercises
• 2.6 Conditional Probability, Independence, and the Product Rule
• Exercises
• 2.7 Bayes’ Rule
• Exercises
• Review Exercises
• 2.8 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 3 Random Variables and Probability Distributions
• 3.1 Concept of a Random Variable
• 3.2 Discrete Probability Distributions
• 3.3 Continuous Probability Distributions
• Exercises
• 3.4 Joint Probability Distributions
• Exercises
• Review Exercises
• 3.5 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 4 Mathematical Expectation
• 4.1 Mean of a Random Variable
• Exercises
• 4.2 Variance and Covariance of Random Variables
• Exercises
• 4.3 Means and Variances of Linear Combinations of Random Variables
• 4.4 Chebyshev’s Theorem
• Exercises
• Review Exercises
• 4.5 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 5 Some Discrete Probability Distributions
• 5.1 Introduction and Motivation
• 5.2 Binomial and Multinomial Distributions
• Exercises
• 5.3 Hypergeometric Distribution
• Exercises
• 5.4 Negative Binomial and Geometric Distributions
• 5.5 Poisson Distribution and the Poisson Process
• Exercises
• Review Exercises
• 5.6 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 6 Some Continuous Probability Distributions
• 6.1 Continuous Uniform Distribution
• 6.2 Normal Distribution
• 6.3 Areas under the Normal Curve
• 6.4 Applications of the Normal Distribution
• Exercises
• 6.5 Normal Approximation to the Binomial
• Exercises
• 6.6 Gamma and Exponential Distributions
• 6.7 Chi-Squared Distribution
• 6.8 Beta Distribution
• 6.9 Lognormal Distribution
• 6.10 Weibull Distribution (Optional)
• Exercises
• Review Exercises
• 6.11 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 7 Functions of Random Variables (Optional)
• 7.1 Introduction
• 7.2 Transformations of Variables
• 7.3 Moments and Moment-Generating Functions
• Exercises
• 8 Fundamental Sampling Distributions and Data Descriptions
• 8.1 Random Sampling
• 8.2 Some Important Statistics
• Exercises
• 8.3 Sampling Distributions
• 8.4 Sampling Distribution of Means and the Central Limit Theorem
• Exercises
• 8.5 Sampling Distribution of S2
• 8.6 t-Distribution
• 8.7 F-Distribution
• 8.8 Quantile and Probability Plots
• Exercises
• Review Exercises
• 8.9 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 9 One- and Two-Sample Estimation Problems
• 9.1 Introduction
• 9.2 Statistical Inference
• 9.3 Classical Methods of Estimation
• 9.4 Single Sample: Estimating the Mean
• 9.5 Standard Error of a Point Estimate
• 9.6 Prediction Intervals
• 9.7 Tolerance Limits
• Exercises
• 9.8 Two Samples: Estimating the Difference between Two Means
• 9.9 Paired Observations
• Exercises
• 9.10 Single Sample: Estimating a Proportion
• 9.11 Two Samples: Estimating the Difference between Two Proportions
• Exercises
• 9.12 Single Sample: Estimating the Variance
• 9.13 Two Samples: Estimating the Ratio of Two Variances
• Exercises
• 9.14 Maximum Likelihood Estimation (Optional)
• Exercises
• Review Exercises
• 9.15 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 10 One- and Two-Sample Tests of Hypotheses
• 10.1 Statistical Hypotheses: General Concepts
• 10.2 Testing a Statistical Hypothesis
• 10.3 The Use of P-Values for Decision Making in Testing Hypotheses
• Exercises
• 10.4 Single Sample: Tests Concerning a Single Mean
• 10.5 Two Samples: Tests on Two Means
• 10.6 Choice of Sample Size for Testing Means
• 10.7 Graphical Methods for Comparing Means
• Exercises
• 10.8 One Sample: Test on a Single Proportion
• 10.9 Two Samples: Tests on Two Proportions
• Exercises
• 10.10 One- and Two-Sample Tests Concerning Variances
• Exercises
• 10.11 Goodness-of-Fit Test
• 10.12 Test for Independence (Categorical Data)
• 10.13 Test for Homogeneity
• 10.14 Two-Sample Case Study
• Exercises
• Review Exercises
• 10.15 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 11 Simple Linear Regression and Correlation
• 11.1 Introduction to Linear Regression
• 11.2 The Simple Linear Regression Model
• 11.3 Least Squares and the Fitted Model
• Exercises
• 11.4 Properties of the Least Squares Estimators
• 11.5 Inferences Concerning the Regression Coefficients
• 11.6 Prediction
• Exercises
• 11.7 Choice of a Regression Model
• 11.8 Analysis-of-Variance Approach
• 11.9 Test for Linearity of Regression: Data with Repeated Observations
• Exercises
• 11.10 Data Plots and Transformations
• 11.11 Simple Linear Regression Case Study
• 11.12 Correlation
• Exercises
• Review Exercises
• 11.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 12 Multiple Linear Regression and Certain Nonlinear Regression Models
• 12.1 Introduction
• 12.2 Estimating the Coefficients
• 12.3 Linear Regression Model Using Matrices
• Exercises
• 12.4 Properties of the Least Squares Estimators
• 12.5 Inferences in Multiple Linear Regression
• Exercises
• 12.6 Choice of a Fitted Model through Hypothesis Testing
• 12.7 Special Case of Orthogonality (Optional)
• Exercises
• 12.8 Categorical or Indicator Variables
• Exercises
• 12.9 Sequential Methods for Model Selection
• 12.10 Study of Residuals and Violation of Assumptions (Model Checking)
• 12.11 Cross Validation, Cp, and Other Criteria for Model Selection
• Exercises
• 12.12 Special Nonlinear Models for Nonideal Conditions
• Exercises
• Review Exercises
• 12.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 13 One-Factor Experiments: General
• 13.1 Analysis-of-Variance Technique
• 13.2 The Strategy of Experimental Design
• 13.3 One-Way Analysis of Variance: Completely Randomized Design (One-Way ANOVA)
• 13.4 Tests for the Equality of Several Variances
• Exercises
• 13.5 Single-Degree-of-Freedom Comparisons
• 13.6 Multiple Comparisons
• Exercises
• 13.7 Comparing a Set of Treatments in Blocks
• 13.8 Randomized Complete Block Designs
• 13.9 Graphical Methods and Model Checking
• 13.10 Data Transformations in Analysis of Variance
• Exercises
• 13.11 Random Effects Models
• 13.12 Case Study
• Exercises
• Review Exercises
• 13.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 14 Factorial Experiments (Two or More Factors)
• 14.1 Introduction
• 14.2 Interaction in the Two-Factor Experiment
• 14.3 Two-Factor Analysis of Variance
• Exercises
• 14.4 Three-Factor Experiments
• Exercises
• 14.5 Factorial Experiments for Random Effects and Mixed Models
• Exercises
• Review Exercises
• 14.6 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 15 2k Factorial Experiments and Fractions
• 15.1 Introduction
• 15.2 The 2k Factorial: Calculation of Effects and Analysis of Variance
• 15.3 Nonreplicated 2k Factorial Experiment
• Exercises
• 15.4 Factorial Experiments in a Regression Setting
• 15.5 The Orthogonal Design
• Exercises
• 15.6 Fractional Factorial Experiments
• 15.7 Analysis of Fractional Factorial Experiments
• Exercises
• 15.8 Higher Fractions and Screening Designs
• 15.9 Construction of Resolution III and IV Designs with 8, 16, and 32 Design Points
• 15.10 Other Two-Level Resolution III Designs; The Plackett-Burman Designs
• 15.11 Introduction to Response Surface Methodology
• 15.12 Robust Parameter Design
• Exercises
• Review Exercises
• 15.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
• 16 Nonparametric Statistics
• 16.1 Nonparametric Tests
• 16.2 Signed-Rank Test
• Exercises
• 16.3 Wilcoxon Rank-Sum Test
• 16.4 Kruskal-Wallis Test
• Exercises
• 16.5 Runs Test
• 16.6 Tolerance Limits
• 16.7 Rank Correlation Coefficient
• Exercises
• Review Exercises
• 17 Statistical Quality Control
• 17.1 Introduction
• 17.2 Nature of the Control Limits
• 17.3 Purposes of the Control Chart
• 17.4 Control Charts for Variables
• 17.5 Control Charts for Attributes
• 17.6 Cusum Control Charts
• Review Exercises
• 18 Bayesian Statistics
• 18.1 Bayesian Concepts
• 18.2 Bayesian Inferences
• 18.3 Bayes Estimates Using Decision Theory Framework
• Exercises
• Bibliography
• Appendix A: Statistical Tables and Proofs
• Appendix B: Answers to Odd-Numbered Non-Review Exercises
• Index
• A
• B
• C
• D
• E
• F
• G
• H
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