Gov 50 (Fall 2022)
  • Syllabus
  • Schedule
  • Materials
  • Assignments
  • Resources
  • Ed
  • Gradescope

Schedule

This content is from Fall 2022. Go to Fall 2023 site

Below is the schedule for the semester. You can find the materials for each course meeting under the “Content” links for that week. You should generally:

  • watch the lecture videos (if any) and complete the readings by Monday;
  • complete the tutorials by Monday evening at 11:59pm; and
  • submit the problem set or exam by Wednesday at 11:59pm.

Here’s a guide to the schedule:

  • Materials (): This page contains the readings, slides, and recorded lectures (if any) for the topic. Read/watch these first.
  • Tutorial (): A link to the tutorial for that week.
  • Assignment (): This page contains the instructions for each assignment. Assignments are due by 11:59 PM on the day they’re listed.

The readings refer to following texts:

  • QSS: Quantitative Social Science: An Introduction in tidyverse by Kosuke Imai and Nora Webb Williams
  • MD: Statistical Inference via Data Science: A ModernDive into R and the Tidyverse by Chester Ismay and Albert Y. Kim
  • IMS: Introduction to Modern Statistics by Mine Çetinkaya-Rundel and Johanna Hardin.
Date Title Reading Materials Tutorial Assignment
Week 0
September 1 Introduction to the course
Week 1
September 6 R, Rstudio, and data visualization MD Ch 1-2
September 7 Tutorial 1  (submit by 23:59:00)
September 8 Data visualization
Week 2
September 12 Tutorial 2  (submit by 23:59:00)
September 13 Data wrangling MD Ch 3
September 14 Problem Set 1  (submit by 23:59:00)
September 15 Data wrangling
Week 3
September 19 Tutorial 3  (submit by 23:59:00)
September 20 Causal inference and randomized experiments QSS Ch 2.1-2.5
September 21 Problem Set 2  (submit by 23:59:00)
September 22 Causal inference and observational studies
Week 4
September 26 Tutorial 4  (submit by 23:59:00)
September 27 Summarizing data QSS Ch 2.6-3.4
September 28 Problem Set 3  (submit by 23:59:00)
September 29 Survey sampling
Week 5
October 3 Tutorial 5  (submit by 23:59:00)
October 4 Summarizing relationships in our data QSS Ch 3.5-3.6
October 5 Problem Set 4  (submit by 23:59:00)
October 6 Importing and joining data MD Ch 4
Week 6
October 11 Prediction & Iteration QSS 4.1 (except 4.1.2)
October 12 Tutorial 6  (submit by 23:59:00)
October 13 Regression MD Ch 5 or QSS 4.2 (except 4.2.5)
October 13–October 16 Exam 1  (submit by 23:59:00)
Week 7
October 18 Multiple regression MD Ch 6.1-6.2 or QSS 4.3.1-4.3.2
October 20 Interpreting regression
October 21 Final Project Milestone 1  (submit by 23:59:00)
Week 8
October 24 Tutorial 7  (submit by 23:59:00)
October 25 Sampling MD Ch 7
October 26 Problem Set 5  (submit by 23:59:00)
October 27 Sampling distributions
October 28 Final Project Milestone 2  (submit by 23:59:00)
Week 9
October 31 Tutorial 8  (submit by 23:59:00)
November 1 The bootstrap and confidence intervals MD Ch 8/IMS Ch 12
November 2 Problem Set 6  (submit by 23:59:00)
November 3 The bootstrap and confidence intervals
Week 10
November 8 Hypothesis testing MD Ch 9/IMS Ch 11
November 9 Problem Set 7  (submit by 23:59:00)
November 10 Hypothesis testing
November 11 Final Project Milestone 3  (submit by 23:59:00)
Week 11
November 15 Hypothesis testing
November 16 Problem Set 8  (submit by 23:59:00)
November 17 Mathematical models of uncertainty IMS Ch 13
November 18 Final Project Milestone 4  (submit by 23:59:00)
Week 12
November 22 Mathematical models of uncertainty
Week 13
November 29 Uncertainty in regression QSS Ch 7.3
December 1 Review Session with TFs
December 1–December 4 Exam 2  (submit by 23:59:00)
Week 14
December 14 Final Project due  (submit by 23:59:00)