Elementary Statistics, 9th edition
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Overview
Hallmark features of this title
 Realworld examples illustrate every concept. You Try It! exercises follow most worked examples, helping students immediately check their understanding.
 Interpretation boxes explain the meaning and significance of statistical results in everyday life and the importance of interpreting results.
 What Does It Mean? boxes explain definitions, formulas and key facts in plain English, and summarize relevant discussions.
 Procedure boxes include the “why, when, and how” of statistical methods.
 Parallel CriticalValue/PValue Approaches enable instructors to focus on one approach or to compare both approaches.
Published by Pearson (June 15th 2022)  Copyright © 2023
ISBN13: 9780137846221
Subject: Introductory Statistics
Category: Elementary Statistics
Table of contents
(NOTE: Each chapter concludes with Chapter in Review, Review Problems, Focusing on Data Analysis, Case Study Discussion, and Biography.)
Technology Resources
Data Sources
I: INTRODUCTION
 The Nature of Statistics
 1.1 Statistics Basics
 1.2 Simple Random Sampling
 1.3 Other Sampling Designs∗
 1.4 Experimental Designs∗
II: DESCRIPTIVE STATISTICS
 Organizing Data
 Case Study: World’s Richest People
 2.1 Variables and Data
 2.2 Organizing Qualitative Data
 2.3 Organizing Quantitative Data
 2.4 Distribution Shapes
 2.5 Misleading Graphs∗
 Descriptive Measures
 Case Study: The Beatles’ Song Length
 3.1 Measures of Center
 3.2 Measures of Variation
 3.3 Chebyshev’s Rule and the Empirical Rule∗
 3.4 The FiveNumber Summary; Boxplots
 3.5 Descriptive Measures for Populations; Use of Samples
 Descriptive Methods in Regression and Correlation
 Case Study: Healthcare: Spending and Outcomes
 4.1 Linear Equations with One Independent Variable
 4.2 The Regression Equation
 4.3 The Coefficient of Determination
 4.4 Linear Correlation
III: PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS
 Probability and Random Variables
 Case Study: Texas Hold ‘em
 5.1 Probability Basics
 5.2 Events
 5.3 Some Rules of Probability
 5.4 Discrete Random Variables and Probability Distributions∗
 5.5 The Mean and Standard Deviation of a Discrete Random Variable∗
 5.6 The Binomial Distribution∗
 The Normal Distribution
 Case Study: Chest Sizes of Scottish Militiamen
 6.1 Introducing Normally Distributed Variables
 6.2 Areas under the Standard Normal Curve
 6.3 Working with Normally Distributed Variables
 6.4 Assessing Normality; Normal Probability Plots
 The Sampling Distribution of the Sample Mean
 Case Study: The Chesapeake and Ohio Freight Study
 7.1 Sampling Error; the Need for Sampling Distributions
 7.2 The Mean and Standard Deviation of the Sample Mean
 7.3 The Sampling Distribution of the Sample Mean
IV: INFERENTIAL STATISTICS
 Confidence Intervals for One Population Mean
 Case Study: Bank Robberies: A Statistical Analysis
 8.1 Estimating a Population Mean
 8.2 Confidence Intervals for One Population Mean When σ Is Known
 8.3 Confidence Intervals for One Population Mean When σ Is Unknown
 Hypothesis Tests for One Population Mean
 Case Study: Gender and Sense of Direction
 9.1 The Nature of Hypothesis Testing
 9.2 CriticalValue Approach to Hypothesis Testing
 9.3 PValue Approach to Hypothesis Testing
 9.4 Hypothesis Tests for One Population Mean When σ Is Known
 9.5 Hypothesis Tests for One Population Mean When σ Is Unknown
 Inferences for Two Population Means
 Case Study: Dexamethasone Therapy and IQ
 10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples
 10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal
 10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal
 10.4 Inferences for Two Population Means, Using Paired Samples
 Inferences for Population Proportions
 Case Study: Arrested Youths
 11.1 Confidence Intervals for One Population Proportion
 11.2 Hypothesis Tests for One Population Proportion
 11.3 Inferences for Two Population Proportions
 ChiSquare Procedures
 Case Study: Eye and Hair Color
 12.1 The ChiSquare Distribution
 12.2 ChiSquare GoodnessofFit Test
 12.3 Contingency Tables; Association
 12.4 ChiSquare Independence Test
 12.5 ChiSquare Homogeneity Test
 Analysis of Variance (ANOVA)
 Case Study: SelfPerception and Physical Activity
 13.1 The FDistribution
 13.2 OneWay ANOVA: The Logic
 13.3 OneWay ANOVA: The Procedure
 Inferential Methods in Regression and Correlation
 Case Study: Shoe Size and Height
 14.1 The Regression Model; Analysis of Residuals
 14.2 Inferences for the Slope of the Population Regression Line
 14.3 Estimation and Prediction
 14.4 Inferences in Correlation
*Indicates optional material.
Appendix A: Statistical Tables
Appendix B: Answers to Selected Exercises
Index
Photo Credits
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