Introductory Guide to R

Více o produktu ↓

Assuming no prior knowledge of programming, this friendly, straightforward guide helps new R users hit the ground running. Eric L. Einspruch provides an overview of this powerful free software and shows how to download and install R, RStudio, and R packages. The book features sample code, screenshots, learning exercises, and worked-through examples of statistical techniques. Fundamental aspects of data wrangling, analysis, visualization, and reporting are introduced, using both Base R and Tidyverse approaches. Einspruch emphasizes processes that support research reproducibility, such as use of comments to document R code and use of R Markdown capabilities.

A friendly, straightforward guide that does not assume knowledge of programming, this book helps new R users hit the ground running. Eric L. Einspruch provides an overview of the software and shows how to download and install R, RStudio, and R packages. Featuring example code, screenshots, tips, learning exercises, and worked-through examples of statistical techniques, the book demonstrates the capabilities and nuances of these powerful free statistical analysis and data visualization tools. Fundamental aspects of data wrangling, analysis, visualization, and reporting are introduced, using both Base R and Tidyverse approaches. Einspruch emphasizes processes that support research reproducibility, such as use of comments to document R code and use of R Markdown capabilities. The book also helps readers navigate the vast array of R resources available to further develop their skills.

Obsah

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