This is an unconventional methods course, because we’ll be looking at two very different kinds of methods in tandem. literature and code. Your work should be balanced between these, so you can think about how to use the methods we learn.
I assume that you have a computer that runs Windows, Mac OS X, or Ubuntu. If you use some more esoteric operating system, I will not help you with installation.
If you do not own a computer or if your computer is unsuitable for the work in this class (as a rule of thumb: if it cost less than $1,000 more than 4 years ago), we can set up an environment in the cloud for you to run RStudio in. I generally don’t advise this, though, because it makes it harder for you to continue your work later.
You should attend class each week having completed the assigned readings and ready to discuss them. Let me know in advance if you are going to be missing class or if you must attend remotely.
To help consolidate your programming abilities, there will be weekly problem sets. The first can be completed in any form you like; later ones should be submitted as PDF, or docx files ‘knitted’ inside R markdown.
Sometimes it will be hard to get them to knit. Post for help on the Slack if you can’t get it to work.
They should be completed weekly, submitted over slack. Problem sets are required but ungraded;
The course text will generally end with a ‘free project’ that presupposes that you are working with your own dataset. We’ll talk about these datasets starting in the second week; in the third week on, you can also use one that I’ll supply of historic New York City population.
These free projects are first stabs towards creating a work of analysis of your own. As we move into the later weeks of the semester, you should figure out which of the the various data sets we’ve used may be particularly interesting and find a way to build out on the techniques and strategies to create something novel. Most likely, this will be an experiment along the lines of the “Quantitative Formalism” pamphlet we read later. In it, you will take the fundamental advantages of a programming environment combine some of the various methods and strategies we’ve learned in a programming environment, or build out some new ones. Appropriate products might include a large-format print map, a set of blog posts exploring generic distances, or a conference-poster style exploration.
This is an advanced graduate seminar; I hope that the syllabus will change in response to your own interests and readings.
This flexibility may cause problems of “versioning”: what version of the syllabus should you believe? So for the record, the priority for what to do consists of:
As graduate students, you should be starting to get a sense of what is important to you; I’m not going to quiz you on individual areas that you read.
But it’s also important that you work consistently in this class for it to be of much use.
I have provided below a default rubric for success in this class. It adds up to 110% because I want you to have some choice for how to distribute your energies.
If you have goals that you feel will not be met here, please meet with me in the first two weeks of class and we can come up with an alternate grade contract.