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An R Companion for Applied Statistics I
Basic Bivariate Techniques

- Danney Rasco - West Texas A&M University, USA

**Other Titles in:**

Quantitative Methods | Research Methods in Psychology | Statistical Computing Environments

**An R Companion for Applied Statistics I: Basic Bivariate Techniques** breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner's *Applied Statistics I, Third Edition*, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.

### Supplements

**Open-access Student Resources**include R code and data sets provided by the author for student download for completing in-chapter exercises.

Rasco's An R Companion to Applied Statistics I is an excellent companion to Warner's seminal statistics text. If you've ever wanted to use R in place of commercial statistics, this is the book that will help you achieve that goal.

**Cornerstone University**

Rasco's text has taken the complexity out of using R for students who are learning the system. His engaging text gives step by step instructions with visuals. He thoroughly covers the relevance and assumptions of each statistical analysis.

**American International College**