Efnisyfirlit

• 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
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X

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