/fried-R-workshop

Teach the fundamentals of programmatic data analysis in R to UChicago undergrads interested in public policy careers

Primary LanguageR

Introduction to Data Analysis in R

Instructor: Cecile Murray, AB 2015, MSCAPP 2020

Assistant: Lilian Huang, AB 2016, MSCAPP 2020

This four-part workshop series is designed to teach the fundamentals of programmatic data analysis in R for the undergraduate students in UChicago's Fried Public Policy and Service Scholars program.

Overview

The series will give students who are interested in public policy careers an introduction to the kinds of data analysis tasks they might encounter in a professional setting and to the fundamentals of performing those tasks in R.

Each workshop will be split between a presentation and a "lab" portion, in which students will have the opportunity to work through a data analysis exercise on their own with the support of their peers and the instructors.

Students will work with real world data from the U.S. Census and from the City of Chicago's open data portal. The exercises will be inspired by the tasks that research assistants and analysts at the nation's leading public policy research institutions perform as the core of their job duties.

The workshop goals are as follows:

  • Help students make the jump from performing data-related tasks Excel to writing code, and demonstrate the strengths and weaknesses of this approach
  • Teach students the fundamentals of data cleaning, assembly, and analysis in R
  • Introduce basic programming concepts such as loops, conditionals, and functions and demonstrate how these concepts can be applied in data analysis

Workshop schedule

  1. Why we use programming for data analysis + getting started in RStudio

  2. Basic data cleaning and assembly, summary statistics, and joins

  3. Data visualization

  4. How to apply key programming concepts for creating scalable, flexible, reusable work product

Resources for R

Interesting datasets