About

Who:

Instructor: Dr. Josef Fruehwald.

Students: People with an interest in data in the arts and sciences. No prior experience in R programming is necessary.

When:

Semester: Spring 2023

Days: Tuesdays & Thursdays, 11:00 to 12:15

Where:

Patterson Office Tower, OB9

What:

This won’t be a course on statistical modelling. Rather, we’ll be focusing on the work you have to do before and after doing any statistics, including

• Basics of R programming

• Finding, organizing, and visualizing your data

• Carrying out exploratory data analysis

• Interacting with the broader programming ecosystem, like using git for version control

• Effectively communicating about your data with authoring tool like Quarto and polished graphics.

Our materials will be largely drawn from free and open source texts, including

• R For Data Science (1st edition https://r4ds.had.co.nz/, 2nd edition https://r4ds.hadley.nz/)

• ggplot2: elegant graphics for data analysis (ggplot2: elegant graphics for data analysis)

• Text Mining with R (https://www.tidytextmining.com/)

• Hands-On Programming with R (https://rstudio-education.github.io/hopr/).