SURV xxx: Introduction to R (Self-Paced Course)

Credit(s)/ECTS: 
0
Core/Elective: 
Elective

R is a powerful language and environment for statistical computing and graphics. This short course will introduce students to R with an emphasis on learning how to install and work in R as accessed through RStudio, a useful wrapper for accessing R. The course will be organized into four general units: 1. a general introduction to R and some useful R vocabulary, 2. a guide for bringing in, manipulating, and exporting data sets, 3. an overview of how to summarize data in R statistically and graphically and 4. a discussion of statistical modeling and advanced topics including designing custom R functions and learning about new R packages. The course is designed to be cumulative, and several topics introduced early on will be referenced in later class discussions.A noted strength and limitation of R is that its functionality is always changing. As such, providedR scripts, particularly those that rely on packages, may not work exactly as shown on the video or may not work at all. This is a hazard of working in R; however, these materials should hopefully be a useful jumping off point for future exploration into R.

Course objectives: 

By the end of the course, students will...

  • install R and Rstudio and be aware of general R vocabulary
  • create different types of objects•import, manipulate and export data•summarize data statistically and graphically
  • run basic statistical models
  • find new packages and packages in the Tidyverse
Grading: 

This course will be ungraded. Quizzes are offered to allow students to assess their knowledge of each unit.

Prerequisites: 

No prerequisites.

Course syllabus: 

Course Dates

2021

Spring Semester (January – May)

Summer Term (June – August)

Fall Semester (September – December)

2022

Spring Semester (January – May)