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

- David S. Brown - University of Colorado, Boulder, USA

**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.

### Supplements

**edge.sagepub.com/brownstats1e**

For additional information, custom options, or to request a personalized walkthrough of these resources, please contact your sales representative. **LMS cartridge included with this title for use in Blackboard, Canvas, Brightspace by Desire2Learn (D2L), and Moodle**

The LMS cartridge makes it easy to import this title’s instructor resources into your learning management system (LMS). These resources include:

- Test banks
- Editable chapter-specific PowerPoint® slides
- All tables and figures from the textbook

**Don’t use an LMS platform?**

You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.

**edge.sagepub.com/brownstats1e**

The open-access Student Study Site makes it easy for students to maximize their study time, anywhere, anytime. It offers datasets and code for use in R.

This book provides a well-written approach to beginning to intermediate-level statistical principles using the R statistical language. It provides some mathematical formulas to help students understand the underlying principles of statistics. It has many excellent social science examples. It provides the statistical understanding with a practical approach to using the most valuable statistical tool—R. Please consider it. I have been looking for a good social science textbook using R—this may be the best so far.

**California State University Los Angeles**

This text successfully presents an introduction to data analysis using R in a highly approachable manner. The use of easy-to-follow examples and conceptual linkage across chapters makes this an outstanding option for undergraduate and graduate stats courses in the social sciences.

**University of Cincinnati**

A great text with in-depth coverage of statistics concepts with helpful R code segments. Great installation directions and rationale for use of R programming versus others.

**Lasell University**

This text takes students on a journey through introductory and intermediate statistical methods along with R programming to accomplish the descriptive and inferential statistics. Images of RStudio and samples of R code are woven throughout the text to help students follow along.

**Florida Gulf Coast University**

An accessible book for any student to learn data analysis, even without a strong math background. It is a student-friendly book that is easy to read, with knowledge checks as the student reads along, and there are great code examples and visualizations that will greatly engage the student.

**University of Nebraska - Lincoln**

Very good book for explain R for students!

**Gatton College of Business & Economics, University Of Kentucky**

The book is an essential reading recommendation for the module as it details the application of R programming language in data visualisation and provides the fundamental statistical knowledge needed for a new student to the world of data analytics. Using this book in the module will help students develop the necessary data analytics knowledge and skills in a friendly and incremental manner.

**Cardiff School of Management, Cardiff Metropolitan University**