The Basic Practice of Statistics

Chapter 0 Getting Started
	0.1 How the Data Were Obtained Matters
	0.2 Always Look at the Data
	0.3 Variation Is Everywhere
	0.4 What Lies Ahead in This Book
	Chapter 0 Exercises
Part I: Exploring Data
	Chapter 1 Picturing Distributions with Graphs
		1.1 Individuals and Variables
		1.2 Categorical Variables: Pie Charts and Bar Graphs
		1.3 Quantitative Variables: Histograms
		1.4 Interpreting Histograms
		1.5 Quantitative Variables: Stemplots
		1.6 Time Plots
		Chapter 1 Summary
		Check Your Skills
		Chapter 1 Exercises
	Chapter 2 Describing Distributions with Numbers
		2.1 Measuring Center: The Mean
		2.2 Measuring Center: The Median
		2.3 Comparing the Mean and the Median
		2.4 Measuring Variability: The Quartiles
		2.5 The Five-Number Summary and Boxplots
		2.6 Spotting Suspected Outliers and Modified Boxplots*
		2.7 Measuring Variability: The Standard Deviation
		2.8 Choosing Measures of Center and Variability
		2.9 Examples of Technology
		2.10 Organizing a Statistical Problem
		Chapter 2 Summary
		Check Your Skills
		Chapter 2 Exercises
	Chapter 3 The Normal Distributions
		3.1 Density Curves
		3.2 Describing Density Curves
		3.3 Normal Distributions
		3.4 The 68–95–99.7 Rule
		3.5 The Standard Normal Distribution
		3.6 Finding Normal Proportions
		3.7 Using the Standard Normal Table
		3.8 Finding a Value Given a Proportion
		Chapter 3 Summary
		Check Your Skills
		Chapter 3 Exercises
	Chapter 4 Scatterplots and Correlation
		4.1 Explanatory and Response Variables
		4.2 Displaying Relationships: Scatterplots
		4.3 Interpreting Scatterplots
		4.4 Adding Categorical Variables to Scatterplots
		4.5 Measuring Linear Association: Correlation
		4.6 Facts about Correlation
		Chapter 4 Summary
		Check Your Skills
		Chapter 4 Exercises
	Chapter 5 Regression
		5.1 Regression Lines
		5.2 The Least-Squares Regression Line
		5.3 Examples of Technology
		5.4 Facts about Least-Squares Regression
		5.5 Residuals
		5.6 Influential Observations
		5.7 Cautions about Correlation and Regression
		5.8 Association Does Not Imply Causation
		5.9 Correlation, Prediction, and Big Data*
		Chapter 5 Summary
		Check Your Skills
		Chapter 5 Exercises
	Chapter 6 Two-Way Tables*
		6.1 Marginal Distributions
		6.2 Conditional Distributions
		6.3 Simpson’s Paradox
		Chapter 6 Summary
		Check Your Skills
		Chapter 6 Exercises
	Chapter 7 Exploring Data:Part I Review
		Part I Summary
		Test Yourself
		Supplementary Exercises
		Online Data for Additional Analyses
Part II: Producing Data
	Chapter 8 Producing Data: Sampling
		8.1 Population versus Sample
		8.2 How to Sample Badly
		8.3 Simple Random Samples
		8.4 Inference about the Population
		8.5 Other Sampling Designs
		8.6 Cautions about Sample Surveys
		8.7 The Impact of Technology
		Chapter 8 Summary
		Check Your Skills
		Chapter 8 Exercises
	Chapter 9 Producing Data: Experiments
		9.1 Observation versus Experiment
		9.2 Subjects, Factors, and Treatments
		9.3 How to Experiment Badly
		9.4 Randomized Comparative Experiments
		9.5 The Logic of Randomized Comparative Experiments
		9.6 Cautions about Experimentation
		9.7 Matched Pairs and Other Block Designs
		Chapter 9 Summary
		Check Your Skills
		Chapter 9 Exercises
	Chapter 10 Data Ethics*
		10.1 Institutional Review Boards
		10.2 Informed Consent
		10.3 Confidentiality
		10.4 Clinical Trials
		10.5 Behavioral and Social Science Experiments
		Chapter 10 Summary
		Chapter 10 Exercises
	Chapter 11 Producing Data: Part II Review
		Part II Summary
		Test Yourself
		Supplementary Exercises
Part III: From Data Production to Inference
	Chapter 12 Introducing Probability
		12.1 The Idea of Probability
		12.2 The Search for Randomness*
		12.3 Probability Models
		12.4 Probability Rules
		12.5 Finite Probability Models
		12.6 Continuous Probability Models
		12.7 Random Variables
		12.8 Personal Probability*
		Chapter 12 Summary
		Check Your Skills
		Chapter 12 Exercises
	Chapter 13 General Rules of Probability*
		13.1 The General Addition Rule
		13.2 Independence and the Multiplication Rule
		13.3 Conditional Probability
		13.4 The General Multiplication Rule
		13.5 Showing Events Are Independent
		13.6 Tree Diagrams
		13.7 Bayes’ Rule*
		Chapter 13 Summary
		Check Your Skills
		Chapter 13 Exercises
	Chapter 14 Binomial Distributions*
		14.1 The Binomial Setting and Binomial Distributions
		14.2 Binomial Distributions in Statistical Sampling
		14.3 Binomial Probabilities
		14.4 Examples of Technology
		14.5 Binomial Mean and Standard Deviation
		14.6 The Normal Approximation to Binomial Distributions
		Chapter 14 Summary
		Check Your Skills
		Chapter 14 Exercises
	Chapter 15 Sampling Distributions
		15.1 Parameters and Statistics
		15.2 Statistical Estimation and the Law of Large Numbers
		15.3 Sampling Distributions
		15.4 The Sampling Distribution of x
		15.5 The Central Limit Theorem
		15.6 Sampling Distributions and Statistical Significance*
		Chapter 15 Summary
		Check Your Skills
		Chapter 15 Exercises
	Chapter 16 Confidence Intervals: The Basics
		16.1 The Reasoning of Statistical Estimation
		16.2 Margin of Error and Confidence Level
		16.3 Confidence Intervals for a Population Mean
		16.4 How Confidence Intervals Behave
		Chapter 16 Summary
		Check Your Skills
		Chapter 16 Exercises
	Chapter 17 Tests of Significance: The Basics
		17.1 The Reasoning of Tests of Significance
		17.2 Stating Hypotheses
		17.3 P-Value and Statistical Significance
		17.4 Tests for a Population Mean
		17.5 Significance from a Table*
		Chapter 17 Summary
		Check Your Skills
		Chapter 17 Exercises
	Chapter 18 Inference in Practice
		18.1 Conditions for Inference in Practice
		18.2 Cautions about Confidence Intervals
		18.3 Cautions about Significance Tests
		18.4 Planning Studies: Sample Size for Confidence Intervals
		18.5 Planning Studies: The Power of a Statistical Test of Significance*
		Chapter 18 Summary
		Check Your Skills
		Chapter 18 Exercises
	Chapter 19 From Data Production to Inference: Part III Review
		Part III Summary
		Test Yourself
		Supplementary Exercises
Part IV: Inference about Variables
	Chapter 20 Inference about a Population Mean
		20.1 Conditions for Inference about a Mean
		20.2 The t Distributions
		20.3 The One-Sample t Confidence Interval
		20.4 The One-Sample t Test
		20.5 Examples of Technology
		20.6 Matched Pairs t Procedures
		20.7 Robustness of t Procedures
		Chapter 20 Summary
		Check Your Skills
		Chapter 20 Exercises
	Chapter 21 Comparing Two Means
		21.1 Two-Sample Problems p
		21.2 Comparing Two Population Means
		21.3 Two-Sample t Procedures
		21.4 Examples of Technology
		21.5 Robustness Again
		21.6 Details of the t Approximation*
		21.7 Avoid the Pooled Two-Sample t Procedures*
		21.8 Avoid Inference about Standard Deviations*
		Chapter 21 Summary
		Check Your Skills
		Chapter 21 Exercises
	Chapter 22 Inference about a Population Proportion
		22.1 The Sample Proportion p
		22.2 Large-Sample Confidence Intervals for a Proportion
		22.3 Choosing the Sample Size
		22.4 Significance Tests for a Proportion
		22.5 Plus Four Confidence Intervals for a Proportion*
		Chapter 22 Summary
		Check Your Skills
		Chapter 22 Exercises
	Chapter 23 Comparing Two Proportions
		23.1 Two-Sample Problems: Proportions
		23.2 The Sampling Distribution of a Difference between Proportions
		23.3 Large-Sample Confidence Intervals for Comparing Proportions
		23.4 Examples of Technology
		23.5 Significance Tests for Comparing Proportions
		23.6 Plus Four Confidence Intervals for Comparing Proportions*
		Chapter 23 Summary
		Check Your Skills
		Chapter 23 Exercises
	Chapter 24 Inference about Variables: Part IV Review
		Part IV Summary
		Test Yourself
		Supplementary Exercises
Part V: Inference about Relationships
	Chapter 25 Two Categorical Variables: The Chi-Square Test
		25.1 Two-Way Tables
		25.2 The Problem of Multiple Comparisons
		25.3 Expected Counts in Two-Way Tables
		25.4 The Chi-Square Statistic
		25.5 Examples of Technology
		25.6 The Chi-Square Distributions
		25.7 Cell Counts Required for the Chi-Square Test
		25.8 Uses of the Chi-Square Test: Independence and Homogeneity
		25.9 The Chi-Square Test for Goodness of Fit*
		Chapter 25 Summary
		Check Your Skills
		Chapter 25 Exercises
	Chapter 26 Inference for Regression
		26.1 Conditions for Regression Inference
		26.2 Estimating the Parameters
		26.3 Examples of Technology
		26.4 Testing the Hypothesis of No Linear Relationship
		26.5 Testing Lack of Correlation
		26.6 Confidence Intervals for the Regression Slope
		26.7 Inference about Prediction
		26.8 Checking the Conditions for Inference
		Chapter 26 Summary
		Check Your Skills
		Chapter 26 Exercises
	Chapter 27 One-Way Analysis of Variance: Comparing Several Means
		27.1 Comparing Several Means
		27.2 The Analysis of Variance F Test
		27.3 Examples of Technology
		27.4 The Idea of Analysis of Variance
		27.5 Conditions for ANOVA
		27.6 F Distributions and Degrees of Freedom
		27.7 Follow-up Analysis: Tukey Pairwise Multiple Comparisons
		27.8 Some Details of ANOVA*
	Chapter 27 Summary
	Check Your Skills
	Chapter 27 Exercises
Part VI: Optional Companion Chapters
	Chapter 28 Nonparametric Tests
		28.1 Comparing Two Samples: The Wilcoxon Rank Sum Test
		28.2 The Normal Approximation for W
		28.3 Examples of Technology
		28.4 What Hypotheses Does Wilcoxon Test?
		28.5 Dealing with Ties in Rank Tests
		28.6 Matched Pairs: The Wilcoxon Signed Rank Test
		28.7 The Normal Approximation for W+
		28.8 Dealing with Ties in the Signed Rank Test
		28.9 Comparing Several Samples: The Kruskal–Wallis Test
		28.10 Hypotheses and Conditions for the Kruskal–Wallis Test
		28.11 The Kruskal–Wallis Test Statistic
		Chapter 28 Summary
		Check Your Skills
		Chapter 28 Exercises
	Chapter 29 Multiple Regression*
		29.1 Adding a Categorical Variable in Regression
		29.2 Estimating Parameters
		29.3 Examples of Technology
		29.4 Inference for Multiple Regression
		29.5 Interaction
		29.6 A Model with Two Regression Lines
		29.7 The General Multiple Linear Regression Mode
		29.8 The Woes of Regression Coefficients
		29.9 A Case Study for Multiple Regression
		29.10 Inference for Regression Parameters
		29.11 Checking the Conditions for Inference
		Chapter 29 Summary
		Check Your Skills
		Chapter 29 Exercises
	Chapter 30 Two-Way Analysis of Variance
		30.1 Beyond One-Way ANOVA
		30.2 Two-Way ANOVA: Conditions, Main Effects, and Interaction
		30.3 Inference for Two-Way ANOVA
		30.4 Some Details of Two-Way ANOVA*
		Chapter 30 Summary
		Check Your Skills
		Chapter 30 Exercises
	Chapter 31 Statistical Process Control
		31.1 Processes
		31.2 Describing Processes
		31.3 The Idea of Statistical Process Control
		31.4 ̄x Charts for Process Monitoring
		31.5 s Charts for Process Monitoring
		31.6 Using Control Charts
		31.7 Setting up Control Charts
		31.8 Comments on Statistical Control
		31.9 Don’t Confuse Control with Capability
		31.10 Control Charts for Sample Proportions
		31.11 Control Limits for p Charts
		Chapter 31 Summary
		Check Your Skills
		Chapter 31 Exercises
	Chapter 32 Resampling: Permutation Tests and the Bootstrap
		32.1 Randomization in Experiments as a Basis for Inference
		32.2 Permutation Tests for Two Treatments with Software
		32.3 Generating Bootstrap Samples
		32.4 Bootstrap Standard Errors and Confidence Intervals
	Chapter 32 Summary
	Check Your Skills
	Chapter 32 Exercises
Back Matter
	Exploring The Web
	Notes and Data Sources
	Tables
		TABLE A Standard Normal Cumulative Proportions
		TABLE B Random Digits
		TABLE C t Distribution Critical Values
		TABLE D Chi-square Distribution Critical Values
		TABLE E Critical Values of the Correlation r
	Answers to Selected Exercises
	Index
		A
		B
		C
		D
		E
		F
		G
		H
		I
		J
		K
		L
		M
		N
		O
		P
		Q
		R
		T
		U
		V
		W
		X
		Z
	Inside Back Cover
	Back Cover