Schedule & Readings

Class Schedule

On Monday and Wednesday we’ll cover new topics and skills, and on Fridays we’ll discuss readings related to those topics. This schedule also includes the topics for the Labs, which will reinforce what we do in class.

I will add Lab links to Github Classroom assignments before each week’s lab. You’ll find a guide to using Github Classroom here.

Date	Mon./Wed. Topics	Lab	Fri. Discussion
	Module 1: Data Basics
Jan. 17-21	What Is Data?; Textbook Ch. 12	Garlic Mustard: 01, 03	Beyond the Hype
Jan. 24-28	NO CLASS MONDAY; Metadata and the Data Analysis Cycle; R Basics	Book Reviews: 01, 03	No class: One-on-one meetings
Jan. 31-Feb. 4	Data Wrangling; Textbook Ch. 5	Movie Dialogue: 01, 03	Ethics, Bias, and Diversity
Feb. 7-11	Visualizing Data; Textbook Ch. 3	Code Glossary I: 01, 03	Ugly, Bad, and Wrong Figures
	Module 2: Describe
Feb. 14-18	Exploratory Data Analysis; Textbook Ch. 7; Hypothesis Testing	Substance Use: 01, 03	An unprecedented Nintendo leak turns into a moral dilemma for archivists
Feb. 21-25	Hypothesis Testing	Audiobooks: 01, 03	Stop Misusing P-Values; Science Isn’t Broken
Feb. 28-Mar.4	Resampling	US Congress I: 01, 03	Ethics, Bias, and Diversity
	Module 3: Predict
Mar. 7-11	Linear Regression	US Congress II: 01, 03	The Happiness Calculator, So About That Thermometer Data
SPRING BREAK
Mar. 21-25	Multiple Regression	Airbnb: 01, 03	Wine and Math
Mar. 28-Apr.1	Network Analysis	Marvel Comics: 01, 03 & Code Glossary II	Outlier Conference
Apr. 4-8	Mapping and Spatial Data	Final Project Launch: 01, 03	NO CLASS; Complete Ethics Certification
Apr. 11-15	Text Data; Textbook Ch. 14	Project Sprints	The Numbers Don’t Speak for Themselves
	Module 4: Communicate
Apr. 18-22	Debugging; Open Data Practices	Project Sprints	Sweet & Slim, Greasy & Grim, Embrace the Grind
Apr. 25-29	Student Presentations	Project Sprints	Student Presentations
May 2	Wrap-up & Advice for Future Students	Troubleshooting and Questions