Preface

1. Introduction
Why R?
Why This Book?
Why the Tidyverse?
What tools are needed?
How This Book Can be Used in a Class
Plan for the Book

2. Foundations
Scripting with R
Understanding R
Working directories
Setting Up an R Project
Loading and Using Packages and Libraries
Where to Get Help
Moving Forward

3. Data Management and Manipulation
Loading Our Data
Data Wrangling
Grouping and Summarizing Your Data (and Using “the Pipe”)
Creating New Variables
Combining Data sets
Basic Descriptive Analysis
Tidying a Data Set
Saving Your Data Set for Later Use
Saving Your Data Set Details for Presentation

4. Visualizing Your Data
The Global Data Set
The Data and Preliminaries
Histograms
Bar Plots
Scatterplots
Combining Multiple Plots
Saving Your Plots
Advanced Visualizations
Parting Thoughts
More Resources

5. Essential Programming
Data Classes
Data Structures
Operators
Conditional Logic
User-Defined Functions
Making your Code Modular
Loops
The map_*() Family from purrr
Concluding Remarks

6. Exploratory Data Analysis
Visual Exploration
Numeric Exploration
Putting it All Together: Skimming Data
Concluding Remarks

7. Essential Statistical Modeling
Loading and Inspecting the Data
t-statistics
Chi-square Test for Contingency Tables
Correlation
Ordinary Least Squares Regression
Binary Response Models
Parting Thoughts

8. Parting Thoughts
Continuing to Learn with R
Where To Go From Here
Final Thought