BOOK
Statistics: The Art and Science of Learning from Data, Global Edition
Alan Agresti | Christine A. Franklin | Bernhard Klingenberg
(2017)
Additional Information
Book Details
Abstract
For courses in introductory statistics.
The Art and Science of Learning from Data
Statistics: The Art and Science of Learning from Data, Fourth Edition, takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises.
The authors believe that it’s important for students to learn and analyze both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data.
MyStatLab™ not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
MyStatLab is an online homework, tutorial, and assessment product designed to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Cover | Cover | ||
| Title Page | 1 | ||
| Copyright Page | 2 | ||
| Dedication | 3 | ||
| Contents | 4 | ||
| Preface | 9 | ||
| Part One Gathering and Exploring Data | 27 | ||
| Chapter 1 Statistics: The Art and Science of Learning from Data | 28 | ||
| 1.1 Using Data to Answer Statistical Questions | 29 | ||
| 1.2 Sample Versus Population | 34 | ||
| 1.3 Using Calculators and Computers | 43 | ||
| Chapter Summary | 49 | ||
| Chapter Problems | 50 | ||
| Chapter 2 Exploring Data with Graphs and Numerical Summaries | 52 | ||
| 2.1 Different Types of Data | 53 | ||
| 2.2 Graphical Summaries of Data | 58 | ||
| 2.3 Measuring the Center of Quantitative Data | 76 | ||
| 2.4 Measuring the Variability of Quantitative Data | 84 | ||
| 2.5 Using Measures of Position to Describe Variability | 92 | ||
| 2.6 Recognizing and Avoiding Misuses of Graphical Summaries | 102 | ||
| Chapter Summary | 108 | ||
| Chapter Problems | 109 | ||
| Chapter 3 Association: Contingency, Correlation, and Regression | 117 | ||
| 3.1 the Association Between Two Categorical Variables | 119 | ||
| 3.2 the Association Between Two Quantitative Variables | 127 | ||
| 3.3 Predicting the Outcome of a Variable | 139 | ||
| 3.4 Cautions in Analyzing Associations | 154 | ||
| Chapter Summary | 170 | ||
| Chapter Problems | 171 | ||
| Chapter 4 Gathering Data | 179 | ||
| 4.1 Experimental and Observational Studies | 180 | ||
| 4.2 Good and Poor Ways to Sample | 188 | ||
| 4.3 Good and Poor Ways to Experiment | 198 | ||
| 4.4 Other Ways to Conduct Experimental and Nonexperimental Studies | 204 | ||
| Chapter Problems | 216 | ||
| Chapter Summary | 216 | ||
| Part Two Probability, Probability Distributions, and Sampling Distributions | 225 | ||
| Chapter 5 Probability in Our Daily Lives | 226 | ||
| 5.1 How Probability Quantifies Randomness | 227 | ||
| 5.2 Finding Probabilities | 234 | ||
| 5.3 Conditional Probability | 247 | ||
| 5.4 Applying the Probability Rules | 258 | ||
| Chapter Summary | 273 | ||
| Chapter Problems | 273 | ||
| Chapter 6 Probability Distributions | 280 | ||
| 6.1 Summarizing Possible Outcomes and Their Probabilities | 281 | ||
| 6.2 Probabilities for Bell-Shaped Distributions | 293 | ||
| 6.3 Probabilities When Each Observation Has Two Possible Outcomes | 305 | ||
| Chapter Summary | 315 | ||
| Chapter Problems | 316 | ||
| Chapter 7 Sampling Distributions | 324 | ||
| 7.1 How Sample Proportions Vary Around the Population Proportion | 325 | ||
| 7.2 How Sample Means Vary Around the Population Mean | 337 | ||
| Chapter Summary | 352 | ||
| Chapter Problems | 352 | ||
| Part Three Inferential Statistics | 359 | ||
| Chapter 8 Statistical Inference: Confidence Intervals | 360 | ||
| 8.1 Point and Interval Estimates of Population Parameters | 361 | ||
| 8.2 Constructing a Confidence Interval to Estimate a Population Proportion | 367 | ||
| 8.3 Constructing a Confidence Interval to Estimate a Population Mean | 380 | ||
| 8.4 Choosing the Sample Size for a Study | 391 | ||
| 8.5 Using Computers to Make New Estimation Methods Possible | 400 | ||
| Chapter Summary | 404 | ||
| Chapter Problems | 404 | ||
| Chapter 9 Statistical Inference: Significance Tests About Hypotheses | 412 | ||
| 9.1 Steps for Performing a Significance Test | 413 | ||
| 9.2 Significance Tests About Proportions | 418 | ||
| 9.3 Significance Tests About Means | 434 | ||
| 9.4 Decisions and Types of Errors in Significance Tests | 444 | ||
| 9.5 Limitations of Significance Tests | 449 | ||
| 9.6 The Likelihood of a Type Ii Error and the Power of a Test | 456 | ||
| Chapter Summary | 463 | ||
| Chapter Problems | 464 | ||
| Chapter 10 Comparing Two Groups | 470 | ||
| 10.1 Categorical Response: Comparing Two Proportions | 472 | ||
| 10.2 Quantitative Response: Comparing Two Means | 486 | ||
| 10.3 Other Ways of Comparing Means, Including a Permutation Test | 498 | ||
| 10.4 Analyzing Dependent Samples | 513 | ||
| 10.5 Adjusting for the Effects of Other Variables | 524 | ||
| Chapter Summary | 530 | ||
| Chapter Problems | 531 | ||
| Part Four Analyzing Association and Extended Statistical Methods | 541 | ||
| Chapter 11 Analyzing the Association Between Categorical Variables | 542 | ||
| 11.1 Independence and Dependence (association) | 543 | ||
| 11.2 Testing Categorical Variables for Independence | 548 | ||
| 11.3 Determining the Strength of the Association | 563 | ||
| 11.4 Using Residuals to Reveal the Pattern of Association | 572 | ||
| 11.5 Fisher’s Exact and Permutation Tests | 576 | ||
| Chapter Problems | 585 | ||
| Chapter Summary | 585 | ||
| Chapter 12 Analyzing the Association Between Quantitative Variables: Regression Analysis | 592 | ||
| 12.1 Modeling How Two Variables Are Related | 593 | ||
| 12.2 Inference About Model Parameters and the Association | 603 | ||
| 12.3 Describing the Strength of Association | 610 | ||
| 12.4 How the Data Vary Around the Regression Line | 620 | ||
| 12.5 Exponential Regression: A Model for Nonlinearity | 631 | ||
| Chapter Summary | 637 | ||
| Chapter Problems | 638 | ||
| Chapter 13 Multiple Regression | 644 | ||
| 13.1 Using Several Variables to Predict a Response | 645 | ||
| 13.2 Extending the Correlation and R2 for Multiple Regression | 651 | ||
| 13.3 Inferences Using Multiple Regression | 657 | ||
| 13.4 Checking a Regression Model Using Residual Plots | 668 | ||
| 13.5 Regression and Categorical Predictors | 674 | ||
| 13.6 Modeling a Categorical Response | 680 | ||
| Chapter Summary | 689 | ||
| Chapter Problems | 690 | ||
| Chapter 14 Comparing Groups: Analysis of Variance Methods | 695 | ||
| 14.1 One-Way ANOVA: Comparing Several Means | 696 | ||
| 14.2 Estimating Differences in Groups for a Single Factor | 706 | ||
| 14.3 Two-Way ANOVA | 716 | ||
| Chapter Problems | 730 | ||
| Chapter Summary | 730 | ||
| Chapter 15 Nonparametric Statistics | 736 | ||
| 15.1 Compare Two Groups by Ranking | 737 | ||
| 15.2 Nonparametric Methods for Several Groups and for Matched Pairs | 748 | ||
| Chapter Summary | 759 | ||
| Chapter Problems | 759 | ||
| Appendix | A-1 | ||
| Answers | A-7 | ||
| Index | I-1 | ||
| Index of Applications | I-9 | ||
| Credits | C-1 | ||
| A Guide to Learning From the Art in This Text | D-1 | ||
| Dataset Files | D-2 | ||
| A Guide to Choosing a Statistical Method | D-3 | ||
| Summary of Key Notations and Formulas | D-4 |