
eBook - ePub
Statistics and Data Visualization Using R
The Art and Practice of Data Analysis
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
About this book
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.
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Statistics and Data Visualization Using R by David S. Brown in PDF and/or ePUB format, as well as other popular books in Social Sciences & Statistics for Business & Economics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Acknowledgements
- Publisher Note
- Title Page
- Copyright Page
- Brief Contents
- Detailed Contents
- Preface
- Acknowledgments
- About the Author
- 1 Getting Started
- 2 An Introduction to Data Analysis
- 3 Describing Data
- 4 Central Tendency and Dispersion
- 5 Univariate and Bivariate Descriptions of Data
- 6 Transforming Data
- 7 Some Principles of Displaying Data
- 8 The Essentials of Probability Theory
- 9 Confidence Intervals and Testing Hypotheses
- 10 Making Comparisons
- 11 Controlled Comparisons
- 12 Linear Regression
- 13 Multiple Regression
- 14 Dummies and Interactions
- 15 Diagnostics I: Is Ordinary Least Squares Appropriate?
- 16 Diagnostics II: Residuals, Leverages, and Measures of Influence
- 17 Logistic Regression
- Appendix: Developing Empirical Implications
- Glossary
- References
- Index