Schedule

Here’s your roadmap for this course!

Before Every Monday’s Class:

  • Lectures (): This contains the lecture slides and video recordings of these lectures. You should watch the videos and follow along for each topic that is assigned per week.

Mondays:

  • Practice (): This page contains an interactive lesson that reinforces the principles that were discussed in the corresponding lecture. They also tend to go through more detail. We will go through this as a class, but you are able to practice on your own, too. Note that I will not be re-lecturing the material; watching the lectures is your homework. 1 out of 1.5 of your participation points each week will come from here! If I ask you questions when we go through material, and it is clear you have not watched the lectures, you will be docked participation.

  • Peer Reviews: You will complete a peer review of your buddy’s code. Instructions can be found on Canvas and are the exact same for every peer review assignment. You have 1.5 days to complete the peer review from after class on Monday. That is, you may complete the peer review between 1pm on Monday to 11:59pm on Tuesday.

Wednesdays:

  • Assignment (): This page contains the instructions for each assignment. All items in the green to-do list boxes are part of the assignment. The entire class period on Wednesdays is dedicated to you doing the assignment. I am around to help when you get stuck. You will need to finish the assignment at home if you do not complete it in class. Assignments are due by 1pm on the following MONDAY Ex: On Wednesday 9/11 you will work on Assignment 1. It covers the lecture material in Week 3 (which you have watched at home and we discussed in class on 9/9). Assignment 1 is due the following MONDAY (9/16) at 11:30am. However, you should be able to complete the vast majority of Assignment 1 during class on Wednesday 9/11. Attendance will be taken on Wednesdays, and will constitute the other .5 points of the 1.5 participation points.

Exceptions to the rule:

  • The first 2 weeks are an exception; normal lecture style
  • Any week where we only have 1 class period, it will be a normal lecture style

tl;dr: You should follow this general process:

  • Watch the Lectures () at home before each Monday’s class
  • Come prepared on Monday to assist the class with the Practice sets ()
  • Come prepared on Wednesday to work your way through each Assignment ()
  • If needed, finish the Assignment () at home, and start watching next week’s Lectures ()

Unit 1: Learning R Lecture Practice Assignment
Weeks 1 & 2: 8/26, 8/29, 9/2 (no class), 9/4 Welcome Lecture Practice Assignment
Syllabus & Installation
R & RStudio
Loading Files
Week 3: 9/9 - 9/11 The Basics Part 1 Lecture Practice Assignment
Objects
Indexing
Objects Part 2
Functions & Help
Week 4: 9/16 - 9/18 The Basics Part 2 Lecture Practice Assignment
Packages
Review and Random
Statistics and Intro to Plotting
Week 5: 9/23 - 9/25 Data Wrangling Lecture Practice Assignment
Introduction to Tidyverse
Using Dplyr
Using Tidyr
Week 6: 9/30 - 10/2 Data Visualization Lecture Practice Assignment
Introduction to Data Visualization
Customizing Your Plots
Multipanel Figures
Layers on Layers on Layers
Week 7: 10/7 (no class) - 10/9 Reproducibility Lecture Practice Assignment
Introduction to RMarkdown
Markdown Anatomy
Endless Flexibility
Unit 2: Statistics Lecture Practice Assignment
Week 8: 10/14 - 10/16 Comparing Means & Stats Issues Lecture Practice Assignment
Comparing Means
Power & Problems
Week 9: 10/21 - 10/23 Relationships Part 1 Lecture Practice Assignment
Correlation
Regression
Week 10: 10/28 - 10/30 Relationships Part 2 Lecture Practice Assignment
Multiple Regression & Interactions
Unit 3: Advanced Topics Lecture Practice Assignment
Week 11: 11/4 - 11/6 AI & Hiring Practices
Week 12: 11/11 - 11/13 Bootstrapping & For Loops
Week 13: 11/18 - 11/20 Writing Functions
Week 14: 11/25 - 11/27 (no class) Data Viz Theory
Week 15: 12/2 - 12/4 Simulations
Due 12/15 Final Project