Statistics in Action teaches a modern approach to statistics that uses graphing calculators or statistical software and allows readers to place more emphasis on statistical concepts and data analysis than on following recipes for calculations. The text is intended to be used as much as a dialog as a reference; readers will have to be thoughtful as they paruse the text. An activity introduces each major topic, allowing readers to experience the major concepts of statistical thinking before going on to confirm them through further analysis (often involving simulation) and practice with data. Statistics in Action gives the design and analysis of both experiments and surveys an honest treatment, rather than forcing them into overly simplistic models.

Table of Contents:
A Note to Students from the Authors vii 1 A CASE STUDY OF STATISTICS IN ACTION 2 1.1 Disctimination in the Workplace: Data Exploration 4 1.2 Discrimination in the Workplace: Inference 11 2 EXPLORING DISTRIBUTIONS 22 2.1 The Shapes of Things: Viusalizing Distributions 24 2.2 Graphical Displays for Distributions 38 2.3 Measures of Center and Spread 53 2.4 The Normal Distribution 79 3 RELATIONSHIPS BETWEEN TWO QUANTITATIVE VARIABLES 100 3.1 Scatterplots 102 3.2 Getting a Line on the Pattern 113 3.3 Correlation: The Strength of a Linear Trend 135 3.4 Diagnostics: Looking for Features That the Summaries MIss 154 3.5 Shape-Changing Transformations 171 4 SAMPLE SURVEYS AND EXPERIMENTS 208 4.1 Why Take Samples, and How Not To 211 4.2 Randomizing: Playing it Safe by Taking Chances 223 4.3 Experiments and Inference about Cause 234 4.4 Dsigning Experiments to Reduce Variability 249 5 SAMPLING DISTRIBUTIONS 266 5.1 Sampling from a Population 268 5.2 Generating Sampling Distributions 274 5.3 Sampling Distribution of the Sample Mean 284 5.4 Sampling Distribution of the Sample Proportion 300 5.5 Sampling Distribution of the Sum and Difference 311 6 PROBABILITY MODELS 326 6.1 Sample Spaces with Equally Likely Outcomes 328 6.2 The Addition Rule and Disjoint Events 339 6.3 Conditional Probability 348 6.4 Independent Events 364 7 PROBABILITY DISTRIBUTIONS 378 7.1 Random Variables and Expected Value 380 7.2 The Bionmial Distribution 391 7.3 The Geometric Distribution 400 8 INFERENCE FOR PROPORTIONS 412 8.1 Estimating a Proportion with Confidence 414 8.2 Testing a Proportion 432 8.3 A Confidence Interval for teh Difference fo Two Proportions 453 8.4 A Significance Test for teh Difference fo Two Proportions 463 9 INFERENCE FOR MEANS 478 9.1 Toward a Confidence Inerval for a Mean 480 9.2 Toward a Significance Test for a Mean 492 9.3 When You Estimate : The t-Distribution 503 9.4 The Effect of Long Tails and Outliers 517 9.5 INference for the Difference Between Two Means 528 9.6 Paired Comparison 547 10 CHI-SQUARE TESTS 576 10.1 Testing a Probability Model: The Chi-Square Goodness-of-Fit Test 578 10.3 The Chi-Square Test of Homogeneity 592 11 INFERENCE FOR REGRESSION 628 11.1 Variation in teh Estimated Slope 631 11.2 Making Inferences about Slopes 643 11.3 Transforming for a Better Fit 658 12 STATISTICS IN ACTION: CASE STUDIES 678 12.1 Mum's the Word! 680 12.2 Baseball: Does Money Buy Success? 683 12.3 Martin v. Westvaco Revisited: Testing for Possible Employment Discrimination 690 Appendix: Statistical Tables 699 Table A: Standard Normal Probabilities 699 Table B: t-Distribution Critical Values 701 Table C: Chi-Square Distribution Critical Values 702 Table D: Random Digits 703 Glossary 704 Brief Answers to Selected Problems 712 Index 743 Photo Credits 752