Data Visualization

Abstract

Are you sick of those drab-looking graphs and plots in Stata and SPSS? We are too! So, this chapter covers data visualization in R. Specifically, you will be working with ggplot2, a package within the tidyverse set of packages, for making high-quality, reproducible graphics. Data visualization is an accessible, aesthetically pleasing, and powerful way to explore, analyze, and convey complex information. It is an integral part of investigating data and disseminating findings to wider audiences. Learning the basics of data visualization in R can improve your workflow and make your findings easier to interpret and more impactful. This chapter reviews how to visually represent nominal and ordinal data using bar charts and how to visualize ratio and interval data using histograms, scatterplots, line graphs, and boxplots in R. Crime data from Greater Manchester, England, will be used to demonstrate these visualization techniques.

Key Terms

Aesthetics

Describe visual characteristics that represent the data.

Data

Information used to answer a research question; typically will be stored in a data frame. Data (plural) are made up of numerous datum (singular).

Geom

Abbreviation for geometries from the ggplot2 package.

Geometries

Describe the objects that represent the data.

Themes

Customizations that can alter the general appearance of a plot.