Statistics and Data Visualization Using R
The Art and Practice of Data Analysis
- David S. Brown - University of Colorado, Boulder, USA
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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
You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
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.
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.
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.
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.
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.
Very good book for explain R for students!
Sample Materials & Chapters
Chapter 2: An Introduction to Data Analysis