David S. Moore George P. McCabe Bruce A. Craig Purdue University
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Library of Congress Control Number: 2016946039
Student Edition Hardcover: ISBN-13: 978-1-319-01338-7 ISBN-10: 1-319-01338-4
Student Edition Loose-leaf: ISBN-13: 978-1-319-01362-2 ISBN-10: 1-319-01362-7
Instructor Complimentary Copy: ISBN-13: 978-1-319-01428-5 ISBN-10: 1-319-01428-3
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Brief Contents
To Teachers: About This Book To Students: What Is Statistics? About the Authors Data Table Index Beyond the Basics Index
PART I Looking at Data CHAPTER 1 Looking at Data—Distributions
CHAPTER 2 Looking at Data—Relationships
CHAPTER 3 Producing Data
PART II Probability and Inference CHAPTER 4 Probability: The Study of Randomness
CHAPTER 5 Sampling Distributions
CHAPTER 6 Introduction to Inference
CHAPTER 7 Inference for Means
CHAPTER 8 Inference for Proportions
PART III Topics in Inference CHAPTER 9 Inference for Categorical Data
CHAPTER 10 Inference for Regression
CHAPTER 11 Multiple Regression
CHAPTER 12 One-Way Analysis of Variance
CHAPTER 13 Two-Way Analysis of Variance Tables Answers to Odd-Numbered Exercises Notes and Data Sources Index
Contents
To Teachers: About This Book To Students: What Is Statistics? About the Authors Data Table Index Beyond the Basics Index
PART I Looking at Data CHAPTER 1 Looking at Data—Distributions Introduction
1.1 Data Key characteristics of a data set
Section 1.1 Summary Section 1.1 Exercises 1.2 Displaying Distributions with Graphs
Categorical variables: Bar graphs and pie charts Quantitative variables: Stemplots and histograms Histograms Data analysis in action: Don’t hang up on me Examining distributions Dealing with outliers Time plots
Section 1.2 Summary Section 1.2 Exercises 1.3 Describing Distributions with Numbers
Measuring center: The mean Measuring center: The median Mean versus median Measuring spread: The quartiles The five-number summary and boxplots The 1.5 × IQR rule for suspected outliers Measuring spread: The standard deviation Properties of the standard deviation Choosing measures of center and spread Changing the unit of measurement
Section 1.3 Summary Section 1.3 Exercises 1.4 Density Curves and Normal Distributions
Density curves
Measuring center and spread for density curves Normal distributions The 68–95–99.7 rule Standardizing observations Normal distribution calculations Using the standard Normal table Inverse Normal calculations Normal quantile plots
Beyond the Basics: Density estimation Section 1.4 Summary Section 1.4 Exercises Chapter 1 Exercises
CHAPTER 2 Looking at Data—Relationships Introduction
2.1 Relationships Examining relationships
Section 2.1 Summary Section 2.1 Exercises 2.2 Scatterplots
Interpreting scatterplots The log transformation Adding categorical variables to scatterplots Scatterplot smoothers Categorical explanatory variables
Section 2.2 Summary Section 2.2 Exercises 2.3 Correlation
The correlation r Properties of correlation
Section 2.3 Summary Section 2.3 Exercises 2.4 Least-Squares Regression
Fitting a line to data Prediction Least-squares regression Interpreting the regression line Facts about least-squares regression Correlation and regression Another view of r2
Section 2.4 Summary Section 2.4 Exercises 2.5 Cautions about Correlation and Regression
Residuals Outliers and influential observations
Beware of the lurking variable Beware of correlations based on averaged data Beware of restricted ranges
Beyond the Basics: Data mining Section 2.5 Summary Section 2.5 Exercises 2.6 Data Analysis for Two-Way Tables
The two-way table Joint distribution Marginal distributions Describing relations in two-way tables Conditional distributions Simpson’s paradox
Section 2.6 Summary Section 2.6 Exercises 2.7 The Question of Causation
Explaining association Establishing causation
Section 2.7 Summary Section 2.7 Exercises Chapter 2 Exercises
CHAPTER 3 Producing Data Introduction
3.1 Sources of Data Anecdotal data Available data Sample surveys and experiments
Section 3.1 Summary Section 3.1 Exercises 3.2 Design of Experiments
Comparative experiments Randomization Randomized comparative experiments How to randomize Randomization using software Randomization using random digits Cautions about experimentation Matched pairs designs Block designs