To Instructors: About This Bookxv
Media and Supplementsxxi
To Students: What Is Statistics?xxiv
Index of Casesxxviii
Index of Data Tablesxxix
Beyond the Basics Indexxxx
About the Authorsxxxi
CHAPTER 1 Examining Distributions1
Introduction1
1.1Data2
1.2Displaying Distributions with Graphs7
1.3Describing Distributions with Numbers23
Case 1.2 Time to Start a Business23
Measuring center: The mean24
Measuring center: The median25
Comparing the mean and the median26
Measuring spread: The quartiles27
The five-number summary and boxplots29
Measuring spread: The standard deviation31
Choosing measures of center and spread32
Beyond the Basics: Risk and Return33
Section 1.3 Summary34
Section 1.3 Exercises35
1.4Density Curves and the Normal Distributions38
Density curves38
The median and mean of a density curve39
Normal distributions42
The 68–95–99.7 rule43
The standard Normal distribution45
Normal distribution calculations46
Using the standard Normal table48
Inverse Normal calculations49
Assessing the Normality of data51
BEYOND THE BASICS: Density Estimation54
Section 1.4 Summary56
Section 1.4 Exercises57
Chapter 1 Review Exercises59
CHAPTER 2 Examining Relationships63
CHAPTER 3 Producing Data123
CHAPTER 4 Probability: The Study of Randomness173
Introduction173
4.1Randomness174
4.2Probability Models179
Sample spaces179
Probability rules182
Assigning probabilities: Finite number of outcomes184
Case 4.1 Uncovering Fraud by Digital Analysis184
Assigning probabilities: Equally likely outcomes186
Independence and the multiplication rule187
Applying the probability rules189
Section 4.2 Summary191
Section 4.2 Exercises191
4.3General Probability Rules194
4.4Random Variables209
4.5Means and Variances of Random Variables219
Chapter 4 Review Exercises239
CHAPTER 5 Distributions for Counts and Proportions243
Introduction243
5.1The Binomial Distributions244
The binomial distributions for sample counts245
The binomial distributions for statistical sampling247
Case 5.1 Inspecting a Supplier’s Products247
Finding binomial probabilities247
Binomial formula250
Binomial mean and standard deviation253
Sample proportions255
Normal approximation for counts and proportions256
The continuity correction260
Assessing binomial assumption with data261
Section 5.1 Summary263
Section 5.1 Exercises264
5.2The Poisson Distributions267
5.3Toward Statistical Inference275
Chapter 5 Review Exercises284
CHAPTER 6 Introduction to Inference287
Introduction287
6.1The Sampling Distribution of a Sample Mean288
6.2Estimating with Confidence302
6.3Tests of Significance316
The reasoning of significance tests316
Case 6.1 Fill the Bottles317
Stating hypotheses319
Test statistics321
P-values322
Statistical significance324
Tests of one population mean326
Two-sided significance tests and confidence intervals329
P-values versus reject-or-not reporting331
Section 6.3 Summary332
Section 6.3 Exercises333
6.4Using Significance Tests336
6.5Power and Inference as a Decision343
Chapter 6 Review Exercises351
CHAPTER 7 Inference for Means357
Introduction357
7.1Inference for the Mean of a Population358
t distributions358
The one-sample t confidence interval360
Case 7.1 Time Spent Using a Smartphone361
The one-sample t test362
Using software365
Matched pairs t procedures368
Robustness of the one-sample t procedures371
BEYOND THE BASICS: The Bootstrap372
Section 7.1 Summary373
Section 7.1 Exercises374
7.2Comparing Two Means378
The two-sample t statistic379
The two-sample t confidence interval381
The two-sample t significance test383
Robustness of the two-sample procedures384
Inference for small samples385
The pooled two-sample t procedures386
Case 7.2 Active versus Failed Retail Companies389
Section 7.2 Summary392
Section 7.2 Exercises393
7.3Additional Topics on Inference398
Chapter 7 Review Exercises411
CHAPTER 8 Inference for Proportions417
Introduction417
8.1Inference for a Single Proportion418
Case 8.1 Robotics and Jobs418
Large-sample confidence interval for a single proportion420
Plus four confidence interval for a single proportion421
Significance test for a single proportion423
Choosing a sample size for a confidence interval426
Case 8.2 Marketing Christmas Trees428
Choosing a sample size for a significance test429
Section 8.1 Summary431
Section 8.1 Exercises432
8.2Comparing Two Proportions436
Large-sample confidence intervals for a difference in proportions437
Case 8.3 Social Media in the Supply Chain438
Plus four confidence intervals for a difference in proportions440
Significance tests440
Choosing a sample size for two sample proportions444
BEYOND THE BASICS: Relative Risk447
Section 8.2 Summary448
Section 8.2 Exercises449
Chapter 8 Review Exercises451
CHAPTER 9 Inference for Categorical Data455
9.1Inference for Two-Way Tables455
Two-way tables456
Case 9.1 Are Flexible Companies More Competitive?457
Describing relations in two-way tables458
The hypothesis: No association462
Expected cell counts462
The chi-square test463
The chi-square test and the z test465
Models for two-way tables466
BEYOND THE BASICS: Meta-Analysis468
Section 9.1 Summary470
9.2Goodness of Fit470
Chapter 9 Review Exercises475
CHAPTER 10 Inference for Regression483
Introduction483
10.1Inference about the Regression Model484
Statistical model for simple linear regression484
From data analysis to inference485
Case 10.1 The Relationship between Income and Education for Entrepreneurs485
Estimating the regression parameters490
Conditions for regression inference494
Confidence intervals and significance tests495
The word “regression”500
Inference about correlation500
Section 10.1 Summary502
Section 10.1 Exercises503
10.2Using the Regression Line510
10.3Some Details of Regression Inference517
Chapter 10 Review Exercises526
CHAPTER 11 Multiple Regression531
Introduction531
11.1Data Analysis for Multiple Regression534
11.2Inference for Multiple Regression548
Multiple linear regression model549
Case 11.2 Predicting Movie Revenue550
Estimating the parameters of the model550
Inference about the regression coefficients551
Inference about prediction554
ANOVA table for multiple regression555
Squared multiple correlation R2558
Inference for a collection of regression coefficients559
Section 11.2 Summary561
Section 11.2 Exercises562
11.3Multiple Regression Model Building566
Chapter 11 Review Exercises584
CHAPTER 12 Statistics for Quality: Control and Capability591
CHAPTER 13 Time Series Forecasting643
CHAPTER 14 One-Way Analysis of Variance711
Introduction711
14.1One-Way Analysis of Variance712
The ANOVA setting712
Comparing means713
The two-sample t statistic714
An overview of ANOVA715
Case 14.1 Tip of the Hat and Wag of the Finger?715
The ANOVA model718
Estimates of population parameters720
Testing hypotheses in one-way ANOVA722
The ANOVA table724
The F test726
Using software729
BEYOND THE BASICS: Testing the Equality of Spread731
Section 14.1 Summary733
14.2Comparing Group Means733
14.3The Power of the ANOVA Test745
Chapter 14 Review Exercises749
Notes and Data SourcesN-1
TablesT-1
Answers to Odd-Numbered ExercisesS-1
IndexI-1
The following optional Companion Chapters can be found online at www.macmillanhighered.com/psbe4e.
CHAPTER 15 Two-Way Analysis of Variance 15-1
CHAPTER 16 Nonparametric Tests 16-1
Introduction16-1
16.1The Wilcoxon Rank Sum Test16-3
Case 16.1 Price Discrimination?16-3
The rank transformation16-4
The Wilcoxon rank sum test16-5
The Normal approximation16-7
What hypotheses do the Wilcoxon test?16-8
Ties16-9
Case 16.2 Consumer Perceptions of Food Safety16-10
Rank versus t tests16-12
Section 16.1 Summary16-12
Section 16.1 Exercises16-12
16.2The Wilcoxon Signed Rank Test16-15
16.3The Kruskal-Wallis Test16-24
Chapter 16 Review Exercises16-29
Notes and Data Sources16-31
Answers to Odd-Numbered Exercises16-32
CHAPTER 17 Logistic Regression 17-1