Introduction to Data Analysis Using R

1. Overview

R is a popular programming language for statistical computing and graphics. This 2-day workshop focuses on the basic concepts and features of R that will serve as building blocks for data analysis tasks. The workshop is taught using RStudio in the Interactive Data Analytics Service (IDAS).

2. Prerequisites

This workshop is for learners who have no experience with R and no experience with computer programming. A basic understanding of general descriptive statistics may be helpful. (See the workshop agenda below.)

3. Eligibility

This workshop is available to current University of Iowa faculty, staff, and students, who are employed by the University or enrolled in a class at the University at the time of the workshop.

4. How to register

Click HERE then log in with your HawkID and password. Click “Register now” at the bottom of the page to register. After registering successfully, an automated email with a Zoom link will be sent to your University of Iowa email. Registration will close at 10 a.m. on Monday, March 18, 2024.

5. Additional information         

If you have any questions, please see the workshop FAQs or contact research-computing@uiowa.edu.

6. Workshop agenda

This workshop is taught in 2 sessions over 2 days. The later session builds on the previous one. Participants are encouraged to attend all sessions to learn the complete contents of the workshop.

Again, note that we start by learning the basic concepts and features of R that will be relevant for data analysis tasks later. If you are already familiar with the concepts below, please see the workshop FAQs for a list of additional, free learning resources.

Tentative topics to be covered:

Day 1

• Introduction and log in to the workshop computing environment
• Brief overview of R and RStudio
• RStudio interface - the Console, Environment, and Files panes
• Getting and setting the working directory
• Working with a script file
• Getting help in R
• Variable assignment
• Built-in functions
• Vectors
• Packages
• Built-in datasets
• Data Frames
• Functions to get basic descriptive statistics
• Factors
• Reading and writing to CSV files

Day 2

• Log in to the workshop computing environment
• Booleans
• Comparison statements
• Brief intro to the tidyverse
• Filter rows
• Create new columns
• Functions to get summary statistics by groups
• Resources for after the workshop