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



October 2021 | 568 pages | SAGE Publications, Inc
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 their 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 more readily see the relationships between variables that are the foundation of quantitative analysis. Through incorporating R and 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 for large datasets, regression, Statistics and Data Visualization Using R quickly gets students new to statistics up to speed running analyses and interpreting data from social science research. This introductory textbook uses social science data from across the U.S. and around the world, from demographic data to opinion research on major social issues to demonstrate the value of statistics to students.

Each figure in the book is accompanied by a Code Chunk box that will reproduce the figure exactly as it’s shown. A copy-and-paste approach to R keeps the focus on the statistics and visualization components, emphasizing that students can easily adjust the code for their own work rather than starting from scratch each time. Features on the Art and Practice of Visualization delve into the process of constructing charts and graphs as well as best practices for data displays. Exercises throughout the book and at the end of each chapter give students ample practice of these new concepts. Give your students a thorough and accessible introduction to R and statistics with Statistics and Data Visualization Using R.

 
Chapter 1 Getting Started
 
Chapter 2 An Introduction to Data Analysis
 
Chapter 3 Describing Data
 
Chapter 4 Central Tendency and Dispersion
 
Chapter 5 Univariate and Bi-variate Descriptions of Data
 
Chapter 6 Transforming Data
 
Chapter 7 Some Principles of Displaying Data
 
Chapter 8 The Essentials of Probability Theory
 
Chapter 9 Confidence Intervals and Testing Hypotheses
 
Chapter 10 Making Comparisons
 
Chapter 11 Controlled Comparisons
 
Chapter 12 Linear Regression
 
Chapter 13 Multiple Regression
 
Chapter 14 Dummies and Interactions
 
Chapter 15 Diagnostics I: Is OLS Appropriate?
 
Chapter 16 Diagnostics II: Residuals, Leverages, and Measures of Influence
 
Chapter 17 Logistic Regression

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Paperback
ISBN: 9781544333861
£96.00