In recognition of Juneteenth, there will be no class on Monday June 20th 2022. There is an assignment due before class to install software and we recommend completing HW 1 (uploading a screenshot showing that you finished the Dataquest module indicated below) before class, but all other assignments will be due July 1st. You are welcome to turn assignments in earlier if you wish.


Day Overview


Time (EST) Content
8:30am - 9:30am Session 1
9:30am - 9:40am Break
9:40am - 10:40am Session 2
10:40am - 10:50am Break
10:50am - 11:50am Session 3


Detailed Schedule + Materials


Day Module Slides Code Resource Cheatsheets/Guides
Day 0 Homework 1 Dataquest
Day 1 Intro HTML, PDF Rmd Day 1 Cheatsheet
RStudio HTML, PDF Rmd Lab, Key, Key HTML
Reproducibility HTML, PDF Rmd Good scientific coding practices
Day 2 Basic R HTML, PDF Rmd Lab, Key, Key HTML Day 2 Cheatsheet
Data IO HTML, PDF Rmd Lab, Key, Key HTML Debugging tips guide
Day 3 Subsetting Data in R HTML, PDF Rmd Lab, Key, Key HTML Day 3 Cheatsheet
Homework 2 Rmd, HTML, Key, Key HTML
Day 4 Data Summarization HTML, PDF Rmd Lab, Key, Key HTML Day 4 Cheatsheet
Data Classes HTML, PDF Rmd Lab, Key, Key HTML
Day 5 Data Cleaning HTML,PDF Rmd Lab, Key, Key HTML Day 5 Cheatsheet
Homework 3 Rmd, HTML, Key, Key HTML
Day 6 Manipulating Data in R HTML, PDF Rmd Lab, Key, Key HTML Day 6 Cheatsheet
Intro to Data Visualization HTML, PDF Rmd Lab, Key, Key HTML
Day 7 Data Visualization HTML, PDF Rmd Lab, Key, Key HTML Day 7 Cheatsheet
Factors HTML, PDF Rmd Lab, Key, Key HTML
Day 8 Statistics HTML, PDF Rmd Lab, Key, Key HTML Day 8 Cheatsheet
Project Guidelines HTML, Rmd Example RMD, Example HTML Instructions
Day 9 Functions HTML, PDF Rmd Lab, Key, Key HTML Day 9 Cheatsheet
Project Guidelines HTML, Rmd Example RMD, Example HTML Instructions

Module Details

Day 0 (before the first session) - Homework 1

Day 1

  • Introduction
  • RStudio
  • Reproducible Research

Day 2

  • Basic R: Variables/Objects in R
  • Data Input/Output

Day 3

  • Subsetting Data
  • Discuss Homework 2 - work on Homework 2 in class if there is time

Day 4

  • Summarization
  • Data Classes

Day 5

  • Data Cleaning
  • Discuss Homework 3 - work on Homework 3 in class if there is time

Day 6

  • Data Manipulation
  • Data Visualization with Esquisse

Day 7

  • Data Visualization Continued
  • Factors

Day 8

  • Statistics
  • Discuss and work on Final Project

Day 9

  • Functions
  • Work on Final Project