An Introductory Guide to R

Eric L. Einspruch, PhD, is an independent researcher and program evaluator based in Oregon. Since the 1980s, Dr. Einspruch has led, managed, and conducted a wide variety of studies to inform policy development and program improvement. As an adjunct professor at Portland State University and elsewhere, he has taught graduate, undergraduate, and certificate courses in the areas of program evaluation, research methods, data analysis, and emergency preparedness. Dr. Einspruch’s work has appeared in peer-reviewed journal articles, books, and book chapters. He is the recipient of Portland State University’s inaugural Adjunct Excellence Award for Research, and, with his coauthors, received the Helen Tobin Writers’ Award for an article published in the Journal for Nurses in Staff Development. Dr. Einspruch was among the organizers of the Oregon Program Evaluators Network, a local affiliate of the American Evaluation Association, and served as its charter secretary during its first 2 years and as its fifth president. He is an avid learner of new ideas, information, and skills who enjoys helping others advance their own learning. His website is www.eleconsulting.com.

1. Introduction
- Purpose of This Book
- What You Will be Able to Do after Reading This Book
- Whom This Book Is For
- Approach
2. Getting Started
- Download and Install R
- Download and Install RStudio
- RStudio Fundamentals
- Download, Install, and Load R Packages
- Read Data into R
- Write Data Files
- Entering Data via Inline Code
- Cleaning Variable Names
- Clearing the Console
- Clearing the Environment
- Some Thoughts on Debugging R Code
3. Data Wrangling
- Example Data
- The Pipe
- Select Variables
- Select Cases
- Missing Data (Part I)
- Recode Variables
- Arithmetic and Logical Operators
- Missing Data (Part II)
- Identify and Change Variable Types
- Change Factor Value Labels
- Join Data Frames
- Aggregate (Summarize) Data
- Wide and Long Data Formats
4. Descriptive Statistics, t-Tests, One-Way ANOVA, and Chi-Square Test
- Descriptive Statistics
- t-Tests
- One-Way ANOVA
- Crosstabulation
5. Factorial ANOVA, Repeated-Measures ANOVA, Correlation, and Regression
- Factorial ANOVA
- Repeated-Measures ANOVA
- Correlation
- Regression
6. Data Visualization
- Layered Grammar of Graphics
- Bar Chart
- Boxplot
- Line Graph
- Scatterplot
- Regression Diagnostics
- Saving a Chart
7. R Markdown
- Markdown Template
- Working in Markdown
8. Functions
9. Next Steps
- Finding Help
- Learn More about R and R Programming
- Community
- Learn More about Statistics
- Updating R, R Packages, and RStudio
10. Conclusion
Appendix A. R Data Structures
Appendix B. Suggested Answers to Exercises
References
Index