Statistics and Data Visualization Using R: The Art and Practice of Data Analysis

 Half Title....2

Acknowledgements....3

Publisher Note....4

Title Page....5

Copyright Page....6

Brief Contents....8

Detailed Contents....9

Preface....26

Acknowledgments....31

About the Author....34

1 Getting Started....35

2 An Introduction to Data Analysis....73

3 Describing Data....114

4 Central Tendency and Dispersion....146

5 Univariate and Bivariate Descriptions of Data....182

6 Transforming Data....227

7 Some Principles of Displaying Data....263

8 The Essentials of Probability Theory....300

9 Confidence Intervals and Testing Hypotheses....341

10 Making Comparisons....376

11 Controlled Comparisons....426

12 Linear Regression....471

13 Multiple Regression....508

14 Dummies and Interactions....542

15 Diagnostics I: Is Ordinary Least Squares Appropriate?....570

16 Diagnostics II: Residuals, Leverages, and Measures of Influence....601

17 Logistic Regression....631

Appendix: Developing Empirical Implications....667

Glossary....672

References....703

Index....721

Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of Data Analysis by David S. Brown teaches students statistics through charts, graphs, and displays of data that help students develop intuition around statistics as well as data visualization skills. By focusing on the visual nature of statistics instead of mathematical proofs and derivations, students can see the relationships between variables that are the foundation of quantitative analysis. Using the latest tools in R and R RStudio® for calculations and data visualization, students learn valuable skills they can take with them into a variety of future careers in the public sector, the private sector, or academia. Starting at the most basic introduction to data and going through most crucial statistical methods, this introductory textbook quickly gets students new to statistics up to speed running analyses and interpreting data from social science research.