Gov 51: Syllabus and Weekly Schedules

Sever Hall 103

Lecture and session attendances are mandatory. Participation (20%) is a significant part of learning for Gov 51 and we will try our best to make your time worth it. You can skip 1 lecture and 1 section without excuses. You can submit 1 problem set late without any excuses.

Jeremiah will hold sections on Wed 10:30 am and Thur 10:30 am. Please download his section syllabus here.

We will mainly reference QSS: An Introduction as our textbook. It is a great textbook for quantitative methods in social science. We will also read tutorials and chapters from other textbooks for certain topics.

Moreoever, Gov 51 will closely follow Gov 50. Gov 50 is the recommended (but not required) pre-requisite for this class. Please see a list of helpful resources by the amazing Prof. Matt Blackwell.

Causal Inference

Linear Regression and Prediction

  • [Week 4] Review
    • Reading: QSS Chapter 4 - Prediction
  • [Week 5] Penalized Regressions and Variable Selection
  • [Week 6] Uncertainty and Inference
  • [Week 7] Midterm Exam: 20%
  • [Week 8] Spring Break
  • [Week 9] Missing Data in Multiple Regression
    • Problem Set II: 10%

Machine Learning Methods

  • [Week 10] Text as Data: Bag of Words
  • [Week 11] Text as Data: Unsupervised Learning
  • [Week 12] Black Box Prediction Methods
  • [Week 13] Network Analysis
    • Problem Set III: 10%

Final Project and Poster Session

  • [Week 14] Final Project Poster Session: 30%

Computing

We’ll use R in this class to conduct data analysis. R is free, open source, and available on all major platforms (including Solaris, so no excuses). RStudio (also free) is a graphical interface to R that is widely used to work with the R language. You can find a virtually endless set of resources for R and RStudio on the internet. For beginners, there are several web-based tutorials. In these, you will be able to learn the basic syntax of R. We’ll post more R resources on the course website.

Accessibility

Harvard University values inclusive excellence and providing equal educational opportunities for all students. Our goal is to remove barriers for disabled students related to inaccessible elements of instruction or design in this course. If reasonable accommodations are necessary to provide access, please contact the Disability Access Office (DAO). Accommodations do not alter fundamental requirements of the course and are not retroactive. Students should request accommodations as early as possible, since they may take time to implement. Students should notify DAO at any time during the semester if adjustments to their communicated accommodation plan are needed.

Mental Health

College is a stressful time in one’s life and mixing it with a global pandemic, remote learning, and dislocation makes this one of the most fraught time any of us have probably faced. Please just get in touch if you are in need of support. Of course, there are other resources at Harvard if you need them. A few are listed below:

Gov 51 and the Data Science Track

Gov 51 counts towards course requirements for the data science track at Harvard. Moreoever, there are more exciting events and lectures by IQSS at Harvard.