Introduction to Data Analysis and Visualization with R*
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.
Agenda
- 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