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Introduction to R for Data Analysis

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Natalie Elphick edited this page Jan 19, 2024 · 30 revisions

Description

The scripting language R is considered one of the most powerful languages for quantitative analysis, statistics, and graphics. This workshop will help you get started using R to analyze your datasets and create graphs for visualization. You'll do hands-on exercises to demystify data analysis using R. This workshop is designed for those who have no background whatsoever in programming/R.

Part 1: The R language and RStudio

  • What is R and why should you use it?
  • The RStudio interface
  • Troubleshooting error messages
  • Variables
  • Types & data structures
  • Math and logic operations
  • Functions and packages
  • Reading data into R

Part 2: Hands-on Data Analysis in R

  • Filtering and reformatting data
  • Exploring data (Basic summaries such as mean, median, etc.)
  • Plotting data
  • R markdown report generation

No background in statistics or computing is necessary. Bring your laptop with RStudio and R installed.

Learning Path

Novice   This is an introductory workshop in the R Scripting series. No prior experience with programming or R/RStudio is required for this course. No prerequisites. Absolute beginners are especially welcome!

Materials

Click here to download the workshop materials.

Pre-workshop Instructions

Before the workshop, complete lesson 0 to install R, RStudio, and the required packages. Please email the instructor if you have any questions or issues.

Online Learning

You can access these materials remotely at any time and go through them at your own pace. Here's how:

  1. Download the materials.

  2. Slides for Part 1

  3. Slides for Part 2

Additional recommended materials for online learning

  1. UCSF library provides an excellent Intro to R module in its Collaborative Learning Environment. It has an instructional video to get started with RStudio, descriptive text, and exercises for practice. All of it is available in a user-friendly online environment. We highly recommend checking this out!

  2. Software carpentry provides well-organized content to get started with R. See here. Absolute beginners may want to focus on modules 1-11 and go through them in two or three sessions.

  3. A searchable list of RStudio webinars and conference talks

  4. Free online books:
    Beginner:
    Hands-on programming with R
    Intro to R
    Intermediate:
    R for Data Science
    ggplot2: elegant graphics for data analysis
    R Markdown: The Definitive Guide
    Advanced:
    Advanced R

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