You should expect this schedule to be a dynamic document. Although the the objectives for this course are fixed, the details of how to accomplish those objectives will depend on the interaction between the instructors and students in the course.
When I make changes, these changes will be recorded in the history of this page on GitHub so that you can track what has changed. I will notify you of changes in class or via email.
I will ask the class for feedback frequently—both in class and anonymously via surveys. Please let me know what is working and what can be improved. I will make adjustments based on this feedback.
Week 1
Introduction
Install software and set up GitHub accounts
Reading
skim after class, I will discuss ideas inspired by these sources:
Matthew Gentzkow and Jesse M. Shapiro. Code and Data for the Social Sciences: A Practitioner’s Guide. March, 2014. Especially Chapter 3: Version Control. The principles of this are good though I don’t follow all their exact prescriptions. The practices adopted for this class are closer to “Good Enough Practices.”
Carlisle Rainey Git for Political Science. Combined with Zach Jones’ article, provides a discussion on Git and GitHub from a political scientist’s point of view.
Roger Peng. Report Writing for Data Science in R for some more discussion of reproducible research (some of which is more relevant to biostatistics than political science) and discussion of R markdown in particular
Review matrix algebra: you should understand what vectors and matrices are. How to add, subtract, and multiply them. And what a matrix inverse is, what it’s properties are. You don’t need to worry about how to calculate a matrix inverse, since you’ll never do that by hand.
Wooldridge appendix
Kahn Academy course Matrices lessons: Introduction, Representing linear systems of equations, elementary matrix row operations, adding and subtracting matrices, multiplying matrices by scalars, properties of matrix addition and scalar multiplication, multiplying matrices by matrices, properties of matrix multiplication, introduction to matrix inverses.