Table Of Contents:
Preface xi
Index of Application xix

PART ONE Variation

Introduction 2(11)

What is Statistics? 2(2)

Previews 4(5)

How to Use This Book 9(4)

Data 13(15)

Data Tables 14(1)

Categorical and Numerical Data 15(2)

Recoding and Aggregation 17(3)

Time Series 20(1)

Further Attributes of Data 21(3)

Chapter Summary 24(4)

Describing Categorical Data 28(24)

Looking at Data 29(2)

Charts of Categorical Data 31(4)

The Area Principle 35(5)

Mode and Median 40(3)

Chapter Summary 43(9)

Describing Numerical Data 52(25)

Summaries of Numerical Variables 53(4)

Histograms and the Distribution of Numerical Data 57(3)

Boxplot 60(2)

Shape of a Distribution 62(4)

Epilog 66(3)

Chapter Summary 69(8)

Association between Categorical Variables 77(27)

Contingency Tables 78(7)

Lurking Variables and Simpson's Paradox 85(4)

Strength of Association 89(6)

Chapter Summary 95(9)

Association between Quantitative Variables 104(46)

Scatterplots 105(2)

Association in Scatterplots 107(2)

Measuring Association 109(6)

Summarizing Association with a Line 115(3)

Spurious Correlation 118(5)

Chapter Summary 123(11)

Statistics in Action Financial time series 134(8)

Statistics in Action Executive compensation 142(8)

PART TWO Probability

Probability 150(24)

From Data to Probability 151(5)

Rules for Probability 156(5)

Independent Events 161(4)

Chapter Summary 165(9)

Conditional Probability 174(22)

From Tables to Probabilities 175(3)

Dependent Events 178(4)

Organizing Probabilities 182(3)

Order in Conditional Probabilities 185(5)

Chapter Summary 190(6)

Random Variables 196(22)

Random Variables 197(3)

Properties of Random Variables 200(5)

Properties of Expected Values 205(2)

Comparing Random Variables 207(2)

Chapter Summary 209(9)

Association between Random Variables 218(25)

Portfolios and Random Variables 219(2)

Joint Probability Distribution 221(3)

Sums of Random Variables 224(1)

Dependence between Random Variables 225(5)

IID Random Variables 230(2)

Weighted Sums 232(4)

Chapter Summary 236(7)

Probability Models for Counts 243(18)

Random Variables for Counts 244(2)

Binomial Model 246(1)

Properties of Binomial Random Variables 247(4)

Poisson Model 251(6)

Chapter Summary 257(4)

The Normal Probability Model 261(43)

Normal Random Variable 262(3)

The Normal Model 265(6)

Percentiles 271(1)

Departures from Normality 272(6)

Chapter Summary 278(9)

Statistics in Action Managing Financial Risk 287(9)

Statistics in Action Modeling Sampling Variation 296(8)

PART THREE Inference

Samples and Surveys 304(21)

Two Surprising Properties of Sampling 305(5)

Variation 310(4)

Alternative Sampling Methods 314(3)

Checklist for Surveys 317(4)

Chapter Summary 321(4)

Sampling Variation and Quality 325(26)

Sampling Distribution of the Mean 326(5)

Control Limits 331(3)

Using a Control Chart 334(3)

Control Charts for Variation 337(6)

Chapter Summary 343(8)

Confidence Intervals 351(27)

Ranges for Parameters 352(5)

Confidence Interval for the Mean 357(3)

Interpreting Confidence Intervals 360(2)

Manipulating Confidence Intervals 362(2)

Margin of Error 364(7)

Chapter Summary 371(7)

Statistical Tests 378(25)

Concepts of Statistical Tests 379(5)

Testing the Proportion 384(4)

Testing the Mean 388(5)

Other Properties of Tests 393(4)

Chapter Summary 397(6)

Alternative Approaches to Inference 403(21)

A Confidence Interval for the Median 404(6)

Transformations 410(1)

Prediction Intervals 411(4)

Proportions Based on Small Samples 415(4)

Chapter Summary 419(5)

Comparison 424(40)

Data for Comparisons 425(2)

Two-sample t-test 427(5)

Confidence Interval for the Difference 432(3)

Other Comparisons 435(9)

Chapter Summary 444(6)

Statistics in Action Rare Events 450(6)

Statistics in Action Testing Association 456(8)

PART FOUR Regression Models

Linear Patterns 464(24)

Fitting a Line to Data 465(2)

Interpreting the Fitted Line 467(5)

Properties of Residuals 472(2)

Explaining Variation 474(1)

Conditions for Simple Regression 475(6)

Chapter Summary 481(7)

Curved Patterns 488(25)

Detecting Nonlinear Patterns 489(2)

Transformations 491(1)

Reciprocal Transformation 492(5)

Logarithm Transformation 497(9)

Chapter Summary 506(7)

The Simple Regression Model 513(32)

The Simple Regression Model 514(4)

Conditions for the Simple Regression Model 518(3)

Inference in Regression 521(8)

Prediction Intervals 529(8)

Chapter Summary 537(8)

Regression Diagnostics 545(28)

Changing Variation 546(9)

Leveraged Outliers 555(4)

Dependent Errors and Time Series 559(7)

Chapter Summary 566(7)

Multiple Regression 573(32)

The Multiple Regression Model 574(1)

Interpreting Multiple Regression 575(6)

Checking Conditions 581(3)

Inference in Multiple Regression 584(4)

Steps in Fitting a Multiple Regression 588(6)

Chapter Summary 594(11)

Building Regression Models 605(30)

Identifying Explanatory Variables 606(5)

Collinearity 611(5)

Removing Explanatory Variables 616(11)

Chapter Summary 627(8)

Categorical Explanatory Variables 635(30)

Two-sample Comparisons 636(3)

Analysis of Covariance 639(3)

Checking Conditions 642(2)

Interactions and Inference 644(7)

Regression with Several Groups 651(5)

Chapter Summary 656(9)

Analysis of Variance 665(29)

Comparing Several Groups 666(7)

Inference in Anova Regression Models 673(4)

Multiple Comparisons 677(3)

Groups of Different Size 680(6)

Chapter Summary 686(8)

Time Series 694(49)

Decomposing a Time Series 695(3)

Regression Models 698(10)

Checking the Model 708(11)

Chapter Summary 719(9)

Statistics in Action Analyzing Experiments 728(8)

Statistics in Action Automated Modeling 736(7)
Appendix: Tables 743
Answers 1(1)
Photo Acknowledgments 1(1)
Index 1