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 four important sections that you should engage with: principles, applications, weekly writings, and assignments.

Overview

The class is structured in the following way: each week, you will have two readings - generally a “principles” first, then an “applications” second. Read the first reading for the Week under Course Content before our first meeting, and the second before our second meeting of the week. In either Tuesday or Thursday class, you’ll be given a prompt for your weekly writing, which is due at 11:59pm on Saturday (see assignments and the syllabus for more info.

  • Principles (): 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.

  • Applications (): 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.

  • Weekly Writings (): Weekly writings are due each week on Saturday at 11:59PM (eastern). Each week’s writing prompt is given during lecture either Tuesday or Thursday

  • Lab 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 following Monday. Labs are in addition to weekly writings and projects.

You should follow this general process (in order) each week:
  • Do everything on the principles () page before Tuesday
  • Come to the lecture on Tuesday.
  • While “in class” on Thursday, work through the applications () 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

Course Calendar

Week Dates Programming Foundations Principles Applications Assignment
1 Aug 26 & Aug 28 (Re-)introduction to R
2 Sep 2 & Seo 4 Programming basics, tidyverse, and visualization
3 Sep 9 & Sep 11 Visualization II
4 Sep 16 & Sep 18 Visualization III
5 Sep 23 & Sep 25 Wrangling Data
Data Analysis Foundations Principles Applications Assignment
6 Sep 30 & Oct 2 Uncertainty and Probability in R
7 Oct 7 & Oct 9 Linear Regression I
Sat Oct 11 Project 1 Due
8 Oct 14 & Oct 16 Linear Regression II
Applications of Data Analysis Principles Applications Assignment
9 Oct 21& Oct 23 In-class Presentation of Project 2
10 Oct 28 & Oct 30 Linear Regression III
11 Nov 4 & Nov 6 Nonlinear Regression
12 Nov 11 & Nov 13 Feature Selection and the Bias Variance Tradeoff
13 Nov 18 & Nov 20 Classification
Nov 22 Project 3 Due
Further Extensions Principles Applications Assignment
14 Nov 25&Nov 27 Text as Data
15 Dec 2 & Dec 4 Geospatial in R (Last lab)
Conclusions Principles Applications Assignment
Dec 10 Final Project Due