sicss-howard-r-boot-camp

Author: Jae Yeon Kim

R boot camp materials for SICSS-HOWARD/Mathematica (2021)

These workshop materials are for your self-study and review. For SICSS-HOWARD participants, this means you don't need to take notes while participating in the boot camp. (Rather spend the time to learn by following along. It would be fun!)

Setup

Click to launch. Please do so before attending the worskshop as it takes a while (especially, if you do it for the first time). To reduce issues related to installation and configuration, I made all workshop materials runnable on docker.

Workshop goals

This workshop aims to introduce and demonstrate how fun and exciting doing data analysis with R could be. Mastering computational tools and techniques not only enable social scientists to collect, wrangle, analyze, and interpret data with less pain and more fun, but it also let them work on research projects that would previously seem impossible. Taking this workshop is the first step to move you in that direction.

Schedule

I believe in the power of deep work (distraction harms concentration, and without concentration, it's challenging to learn complex technical subjects.) So, even though the workshop is virtual, please try to stay away from distractions for at least six hours (we will take a break every hour to help you rehydrated or decaffeinated, depending on your preferences.).

Day 1 (3 hours)

Learning objectives:

• How R (the programming language) and R studio (integrated development environment) work
• Getting the big picture (the two main building blocks) of programming: objects and functions
• Importing and exporting files in a reproducible way
• Playing with data types (the bread and butter of data analysis): vectors (numeric, character, factor, logical), dataframes, and lists

Day 2 (3 hours)

Learning objectives:

• Understanding the master framework: tidy principles
• Wrangling messy data quickly and easily
• Running statistical model quickly and easily
• Plotting data and model quickly and easily

Additioinal resources

This workshop helps you get up and started in R programming and data analysis and aims to expose you to the landscape of the R ecosystem. However, it certainly doesn't cover all important subjects in-depth. If you are interested in learning further, I recommend taking a look at my working-version textbook on learning computational methods focusing on R. This workshop is a condensed version of the earlier part of the textbook.

Special thanks

This workshop is a condensed remix version of the course originally developed by Rochelle Terman then revised by Rachel Bernhard and me. Other teaching materials draw from the workshops I hvae created for D-Lab and Data Science Discovery Program at UC Berkeley.

This work is licensed under a Creative Commons Attribution 4.0 International License.