Available Until 10/31/2028

Introduction to Data Analysis and Visualization with R*


For more information or to schedule this course, please contact Lisa Federer <lisa.federer@nih.gov>.

So you’ve heard about R – how it will help you with your statistical analyses, create beautiful graphs, and make your science more reproducible – but you’ve never written a line of code in your life. Don’t be scared! In this face-to-face course especially for non-programmers, you’ll learn the basics to get started with using R. We’ll use RStudio, a user-friendly interface for R, and cover topics including: • Key terminology and concepts • Essentials of data processing • Basic statistical analysis • Creating simple graphics

Learning Objectives

After completing this course, learners will understand how to use R, an open source programming language, to work with a variety of different types of data, including library related data, scientific research data, and clinical data. Specifically, learners will be able to use R to:

•organize and “wrangle” (or clean) data

•conduct basic data and statistical analyses

• create exploratory and publication-ready visualizations.


-	Why R? Applications and uses: 5 minutes
-	Key terminology, concepts, and syntax: 10 minutes
-	Data processing and analysis: 1.5 hours
o	Understanding data structures
o	Data “wrangling”: organizing and cleaning messy data
o	Basic statistical analysis
-	Break: 15 minutes
-	Data visualization: 1.5 hours
o	The Grammar of Graphics: a framework for building data visualizations
o	Exploratory data visualization
o	Creating publication-ready visualizations
o	Customizing color and appearance
-	Questions and next steps for learning more: 30 minutes

Facility Requirements

Computers (preferably with internet access) with R and RStudio software (free and open source, but both require installation), one for each attendee and one for the instructor.

MLA CE Credits: 4