Schedule

Below is a roadmap for the semester. Note that this will inevitably change from the first day you access this course. However, whatever is listed below should be considered canon. Accordingly, you should visit this page frequently throughout the term.

As mentioned in the syllabus, the course is structured by topics; each week introduces a new topic. Moreover, every week is divided into three important sections that you should engage with.

Overview

The class is structured with three distinct bits. First, the Tuesday lecture will give an overview of the topic for the week. Next, the Thursday lecture will have a short, practical lecture and an activity which is designed to give you hands-on experience and a greater understanding of the broader material. Finally, you will complete weekly writings (short) and labs (also somewhat short; requiring coding in R). Out of class, you will complete readings and complete assignments.

  • Content (): This page contains the readings for the topic. These pages should be read completely. Lectures are not an exact replication of the written content; on the contrary, the lectures are intended to keep you focused on the high-level ideas, while the readings are broader and more comprehensive. Accordingly, lectures are shorter than the (often quite lengthy) written content.

  • Examples (): This page the material that we will discuss in Thursday classes. In addition to teaching specific content, there are many more R code examples. These are intended as a useful reference to various functions that you will need when working on (nearly) weekly labs and your group project.

  • Assignments (): This page contains the instructions for the weekly lab (1–3 brief tasks) and for the two mini projects + final project. Labs are due by 11:59 PM (Eastern) on the Monday after they’re posted. Labs are in addition to weekly writings and projects.

tl;dr: You should follow this general process (in order) each week:

  • Do everything on the content () page before Tuesday
  • Come to the lecture on Tuesday.
  • While “in class” on Thursday, work through the example () page
  • Complete the weekly writing by Saturday - topic assigned in class, see assignments for details and template
  • Complete the lab () by Monday.
  • As needed, attend the lab hours hosted by the TA.

Programming Foundations Content Example Assignment
Week 0 (Aug 29 / Sep 1) (Re-) Introduction to R
Week 1 (Sep 5/7) Programming Basics, the tidyverse, and Visualization
Week 2 (Sep 12/14) Visualization II
Week 3 (Sep 19/21) Visualization III
Data Analysis Foundations Content Example Assignment
Week 4 (Sep 26/28) Uncertainty and Probability in R
Week 5 (Oct 3/5) Linear Regression I
Week 6 (Oct 10/12) Linear Regression II
Saturday Oct 14th Project 1 Due
Week 7 (Oct 17/19) Linear Regression III
Applications of Data Analysis Content Example Assignment
Week 8 (Oct !24/27) LASSO: Least Absolute Shrinkage and Selection
Week 9 (Oct 31 / Nov 2) Nonlinear Regression
Week 10 (Nov 7/11) Bias vs Variance (No lab this week)
Week 11 (Nov 14/16) Classification
Saturday Nov 18th Project 2 Due
Further Extensions Content Example Assignment
Week 12 (Nov 21/!23) Text as Data
Week 13 (Nov 28/30) Wrangling Data
Week 14 (Dec 5/7) Geospatial in R (Last lab)
Conclusions Content Example Assignment
Thursday Dec 14th, 11:59pm Final Project Due