I Spot a Cool Plot: A Nearly Syntax-Free Introduction to Advanced Data Visualization in R for Survey Researchers and Social Scientists

Image of a professor presenting to a classroom.
I Spot a Cool Plot: A Nearly Syntax-Free Introduction to Advanced Data Visualization in R for Survey Researchers and Social Scientists

I Spot a Cool Plot: A Nearly Syntax-Free Introduction to Advanced Data Visualization in R for Survey Researchers and Social Scientists

When

October 12, 2022    
12:00 pm - 4:00 pm

Where

-->

This online workshop will introduce attendees to the advanced data visualization capabilities in R and to the concepts of the grammar of graphics. Specifically, we will demonstrate how to access ggplot2 using a graphical user interface library in R as well as through an R shiny app. These environments provide the user a “point and click” interface for accessing the power of ggplot2 and can generate R syntax automatically thereby providing users a boost up the learning curve for understanding the grammar of graphics used by ggplot2.

We begin the workshop with an overview of the grammar of graphics and explain how graphs are constructed in layers and aesthetics which will lay a foundation for how to approach creating advanced graphics and visualizations. We will then demonstrate how to create and export various kinds of visualizations including violin pots, line plots, boxplots, scatterplots, bubble plots, bar charts, histograms and more using these interfaces. The examples used throughout will leverage mixed data types (e.g. a combination of continuous and categorical variables) that are common in both survey research and social sciences.

While no prior R programming experience is assumed, a working understanding of the R environment (how to load packages, etc.) or Rstudio will be very helpful. Having the most recent version of R and /or Rstudio and an internet connection during the workshop would help users follow along in real time if desired.

Instructor: Trent Buskirk, PhD
Trent D. Buskirk, PhD, is the Novak Family Professor of Data Science and the Chair of the Applied Statistics and Operations Research Department at Bowling Green State University. Trent received his PhD in Statistics from Arizona State University with emphasis in Survey Sampling. Since that time he has developed specific expertise in Mobile and Smartphone Survey Designs and Data and in the use of machine learning methods for developing sampling designs and adaptive survey protocols. Trent has held positions in academia and industry including Director of the Center for Survey Research at UMass Boston and as an Associate Professor of Biostatistics at Saint Louis University as well as the Research Director in Measurement Science for the Nielsen Company and Vice President or Methods and Statistics at the Marketing Systems group.