Elizabeth Gohmert graduated from Texas A&M University in 2018 with a Bachelor of Arts in Political Science
and a minor in Cybersecurity-a year early. She then went on to graduate school at Southern Methodist
University, from which she graduated with a Master of Science in Business Analytics in 2019. While she
had previously helped to edit the book, "Using R for Data Analysis in Social Sciences", this will be her first
authored publication. Aside from her love of data science, she enjoys travelling, learning new languages,
white water rafting, and the joy of finding great new rib places. She currently lives and works in Washington,
D.C. as a data science consultant.

Preface
Why Should You Learn R Too?
Who Should Read This Book? What Does This Book Hope to Achieve?
What Is in This Book? How Can You Use It?
What Is Unique About This Book?
Acknowledgments
About the Authors
CHAPTER 1 ¿ Making Preparations: Software Installation and Project Setup
1.1 Introduction
1.2 How to Download and Install R for Windows
1.3 How to Download and Install R for Mac
1.4 Downloading and Installing RStudio
1.5 Setting Up a Project in RStudio
1.6 Creating Folders Under a Project
1.7 Summary
1.8 References
CHAPTER 2 ¿ Writing Your Essay Using R Markdown: Something for Everyone
2.1 Introduction
2.2 The Pros of Using R Markdown
2.3 How to Create an R Markdown File
2.4 How to Write and Format Text in R Markdown
2.5 A Simple Example of an R Markdown Document
2.6 Other Useful Formatting Tricks
2.7 How to Use R Markdown for a Writing Assignment: A Bare-Bones Example
2.8 How to Revise and Improve Your Bare-Bones Essay
2.9 For More Ambitious Readers
2.10 Exercise: Turning Knowledge Into Results
2.11 Summary
2.12 References
CHAPTER 3 ¿ Creating Data and Graphs in Your Essays
3.1 Introduction
3.2 Bar Plot I: Graphing the Winners of a Hot Dog Eating Contest
3.3 Bar Plot II: Graphing Winning Lottery Numbers in Texas Pick-3
3.4 Pie Chart: Graphing the Composition of Daily Plays Among Top 5 Songs on Spotify
3.5 Histogram: Graphing the Distribution of LSAT Scores in a Review Class
3.6 Scatter Plot: Graphing the Relationship Between Two Variables- Gas Mileages in the City and on the Highway
3.7 Time Series Plot: Graphing the Changing Pattern of YouTube Video Views
3.8 Useful Tips: Polishing and Exporting Graphs
3.9 Summary
3.10 References
CHAPTER 4 ¿ Preparing Your Data
4.1 Introduction
4.2 Writing and Running a Program in R
4.3 Creating Variables and Forming a Dataset
4.4 Manipulating Data Using the dplyr Package
4.5 Chaining Different Data Manipulation Operations: pipe (%>%)
4.6 Missing Values in R: NA
4.7 Summary
4.8 References
CHAPTER 5 ¿ Accessing Datasets
5.1 Introduction
5.2 Setting Up an RStudio Project
5.3 Downloading a Dataset
5.4 Installing R Packages for Data Importing
5.5 Importing a Downloaded Dataset in RStudio
5.6 Using R Data Packages: A Simple Example With gapminder
5.7 Using R Data Packages: A More Advanced Example With wbstats
5.8 Using R Data Packages: Finding More R Data Packages
5.9 Where Can You Find More Data?
5.10 Summary
5.11 References
CHAPTER 6 ¿ Exploratory Data Analysis: Three Exercises
6.1 Introduction
6.2 Exercise 1: Reporting Results of the 2016 Presidential Primary in King County, Washington
6.3 Exercise 2: Human Use of Natural Resources: Consumption and Biocapacity
6.4 Exercise 3: Exploring the Impact of GDP per Capita on Life Expectancy
6.5 Summary
6.6 References
CHAPTER 7 ¿ Writing Your Research Paper Using R: Analyzing the Effect of Economic Development on Life Expectancy