I’m teaching two classes this semester:
– Design and Analysis of Sample Surveys (in the political science department, but the course has lots of statistics content);
– Statistical Communication and Graphics (in the statistics department, but last time I taught it, many of the students were from other fields).
I’ve taught both classes before. I taught Statistical Communication last semester. It went well and I’m rearranging it a bit for the spring. It should go well.
I’ve taught Design and Analysis of Sample Surveys twice before, and each time the students have wanted a bit more statistics and a bit less social science. Most of the students in the class are studying political science but they can get that from the other profs in their program; when they take my course they’re looking for the hard statistics stuff they can’t get anywhere else. Their favorite part of the course was when I taught them about practical regression modeling.
These exam questions should give you an idea of what was in my surveys class before. It’s ok but this time I’m going to go lighter on the traditional sampling topics (ratio and regression estimation, stratified cluster sampling bla bla bla) and instead have them do Mister P for real in R and Stan, just like the grownups do. These are Columbia grad students, for chrissake—I don’t know what I was thinking before. If they don’t learn serious survey analysis now, when will they?
Don’t get me wrong here. I won’t teach only MRP. But it will flow naturally from (a) regression modeling, and (b) the goal of using a sample to make inferences for the population. From this perspective, it would be perverse to teach regression and sample surveys and not show them how to do MRP. And, once they’re fitting multilevel models, it makes sense to do it in Stan, since that’s what everybody’s gonna be using soon anyway.
OK, so here’s the deal. In revamping my Design and Analysis of Sample Surveys, I need to fix two things:
1. The course material. Less of the boring classical stuff that I used to force myself to teach and force the students to remember (for example, the expression for the standard error of the ratio estimate) and more of the good stuff. To get more specific, I need to write some R and Stan code to do MRP in some simple examples, I need to get the relevant census data together, etc. And of course I need to put this in the context of 14 weeks of class.
2. The classroom experience. Me standing up and talking in front of a class of 25 students? What a joke. Anything important I can say, I can write instead, and the students can read (remember, they’re Columbia grad students: if they can read AJPS papers, they can read whatever tutorial material I write). Classroom time is mostly wasted unless it involves active student learning. I know this in the context of my other course, now it’s time to walk the walk and do it for all my other classes. Starting with this one.
What to do during those 28 sessions, each 75 minutes long?
But . . . what should I actually do in class? I’m not sure. The first week of class I can lecture and have discussion, that’s no problem, the students need to get a sense of what’s coming and why it’s important. I guess I should prepare a few work-in-pairs problems, though. Then, after that first week, their homework assignments will start to come in, and we can spend time on that.
I’ll require that students bring their laptops to every class so that, whenever we want, we can break them out and start working. More efficient to get their R and Stan issues resolved in 15 minutes during class than during tearful overnight sessions at home.
I still think I need a specific plan, though.
It goes like this: Each week we have topics, readings, homeworks, and the skills and concepts I want the students to learn. This all drives the class period. I’ll prepare some slides to spark discussion.
No fear of dead time. That’s important. The students have tons that they have to figure out, that they ultimately have to work out for themselves. Two 75-minute periods a week are not a lot of time, it’s precious time for me to help them out.
So, I still need to make a plan for how to spend each class, starting in week 2.
In the meantime, here’s my current schedule of topics for the 14 weeks of class. Any comments are appreciated.
Introduction (week 1):
1a: Overview of the course
1b: Examples of surveys in the news
Statistics review (weeks 2–4)
2a: Basic statistics
2b: Statistical inference in the context of large variation
3a: Linear regression
3b: Logistic regression
4a: Statistical graphics
4b: Causal inference
Classical design and analysis of surveys (weeks 5–7)
5a: Survey interviewing
5b: Survey measurement
6a: Simple and stratified random sampling
6b: Weighting and poststratification
7a: Cluster sampling
7b: Analysis of data from cluster sampling
Social and political science (weeks 8–10)
8a: Surveys in the United States
8b: Surveys in other countries
9a: Voting and political participation
9b: Public opinion
10a: Network sampling
10b: Survey experiments
Advanced analysis of survey data (weeks 11–14)
11a: Bayesian regression
11b: Multilevel modeling
12a: Item-response and ideal-point modeling
12b: Multilevel regression and poststratification
13a: Constructing survey weights
13b: Missing-data imputation
14a: Open problems in analysis of survey data
14b: Summary of the course
Maybe we should do some role-playing activities? Maybe the students should design and conduct a survey together? I don’t know.