* R Short Courses are for current UT faculty, staff, and students.


* Seating for each class is limited to 40 students.

 Instructors: Michael Mahometa and Sally Ragsdale are statistical consultants for the Department of Statistics and Data Sciences.  Full Bios

 

Introduction to R

This course introduces R, a free and open-source software package used for statistical computing and graphics. We will cover navigating the free graphical user interface RStudio, importing and exporting data, creating and manipulating variables, and basic data analyses and graphics. In addition, the course will introduce installation of R packages and familiarize participants with built-in help documentation and online resources. 



After completing this course, a new user should be able to:

  • Navigate RStudio.
  • Import/export data from/to external files.
  • Create and manipulate new variables.
  • Conduct basic statistical analyses (t-tests, chi-square tests, linear regression).
  • Create basic graphs.
  • Install and use R packages.


Prerequisites: Familiarity with basic statistical concepts such as t-tests and regression is 
recommended but not necessary.

 

R - Analysis

This short course covers data analysis in R in greater depth than the introductory course.  For various statistical methods (see list below), participants will learn how to prepare a dataset, test relevant assumptions, and carry out the analyses. Although some time will be spent on interpretation, this hands-on course will teach participants how to use R to run different types of analysis, rather than the methods themselves.

After completing this course, participants should be able to carry out the following analyses in R:

  • Correlation and simple linear regression.
  • Chi-squared tests.
  • T-tests and one-way ANOVA.
  • Multiple regression and multivariate ANOVA models.
  • Logistic regression.
  • Linear and logistic mixed models/HLM/multilevel models.

Prerequisites: Completion of "Introduction to R" short course or equivalent knowledge and experience with R and RStudio. Participants who have familiarity with the above topics will get the most out of this course.

 

R - Graphics

This course covers basic plotting and more advanced graphic capabilities in R.  We will cover graphical displays commonly used in publications for various statistical analysis methods and learn how to edit plot features.  In addition, participants will learn how to use the ggplot2 package.

After completing this course, participants should be able to:

  • Graphically display various types of data.
  • Edit features of graphs (titles/labels, colors, shading, etc.).
  • Make graphs using ggplot2.

Prerequisites: Completion of "Introduction to R" short course or equivalent knowledge and experience with R and RStudio.