Introduction to R

April 13, 2017

9:00am - 5:00pm

DBH 4011

Instructors: Emma Smith, Chris Galbraith

TAs: Kevin Cochran


This course provides an introduction to the fundamentals of the R language and its applications to data analysis.

In this course, you will learn how to program in R and how to effectively use R for data analysis. The course covers introduction to data/object types in R, reading data, creating data visualizations, accessing and installing R packages, writing R functions, fitting statistical models including regression models and performing statistical tests including t-tests and ANOVA. Practical examples will be provided during the course.

Who: The course is aimed at graudate students and other researchers from non-ICS schools. You don’t need to have any previous knowledge of the tools that will be presented at the workshop.

Requirements: Participants must bring a laptop with a few specific software packages installed (see Pre-Workshop Instructions).

Prerequisites: Some programming experience is recommended.

Contact: Please email or for more information.

Tentative Schedule

8:30-9:00 Sign-in & Coffee/Bagels
9:00-12:30 Instruction
12:30-1:00 Lunch
1:00-2:30 Instruction
2:30-2:45 Break with Coffee/Drinks
3:00-5:00 Final Instruction


  • Data Types in R
  • Control Structures and Functions
  • Statistical Distributions in R
  • Exercises: Basic Data Exploration
  • Statistical Analysis in R
  • Plotting and Data Visualization in R
  • Data visualization & Statistical Analysis

Pre-Workshop Instructions

Step 1: Download and install R

First, visit The R Project for Statistical Computing’s website through Click on “CRAN” under the Download section on the left-hand side of the page. Then, click on any of the nearby websites under the USA section near the bottom of the page. For example, the link from the University of California, Berkley, CA or University of California, Los Angeles, CA are both fine. Download R for your platform (Linux, Mac, or Windows).

Step 2: Download and install RStudio

RStudio is a set of integrated tools designed to help you be more productive with R; it is known to be more user-friendly. You will be doing essentially all of your programming in RStudio. To download RStudio, go to Download the installer for your platform under “Installers for Supported Platforms”.

Step 3: Installing packages

After installing R and RStudio, open RStudio. Not all functions have been installed in R, so utilizing certain functions requires you to install a package and ``open’’ that package every time you open a new R session. There are two ways to install packages in RStudio.

  • Method 1: Find your console (for first-time R users, the console is located at the bottom-left of RStudio’s interface). Then type the following code and press Ctrl + Enter or Run (the quotation marks are needed between the package name):
R> install.packages("PackageName", dependencies = TRUE)
  • Method 2: On RStudio’s taskbar, click on “Tools” and then “Install Packages…” Afterwards, put down the name of the package(s) you wish to install and click install.

Github Repo