Thoughts on Other Course - Gov2001

4 Apr 2011

Gov2001,

I got the following question from Julie over the weekend (which I reprint
here with her permission):

"I am wondering if you guys have any advice for another stats course I
should take next. While I feel fairly comfortable with the material covered
in GOV2000 and GOV2001, I kind of just want to go over it all again and get
more practice applying this stuff. Any suggestions?"

I figured others might be interested in the answers as well (hence the email
to the list).

First, let me say that I think this question is posed in exactly the right
way.  Even though you are "comfortable" with the material in 2000 and 2001
its useful to learn it again in another setting.  When I've spoken with Gary
about his methods education in grad school, that's what he told me he did.
 He just went to a bunch of different departments and took classes teaching
basically the same material from different traditions.  So just because
you've already covered Generalized Linear Models in this class doesn't mean
you should shy away from taking a GLMs course in the stats department.

Let me start by giving the short, direct answer: Stat 149/249 is the
statistics department equivalent of this class.  It covers generalized
linear models from quite a different perspective (closely following the
canonical textbook McCullagh and Nelder if that helps).  If you want to
review material in this class and get more practice.  This is the way to do
it.

Now for the longer answer.  Generally speaking the major choice you have to
make is which department to take the class in.  The economics perspective is
very different from the statistics perspective (for example).  In fact you
see the hallmarks of both traditions in political science.   My background
has favored that statistical over the econometric approach, so my apologies
if my answer is a bit biased (note my answer is also poli-sci biased and
Harvard-centric because that is what I know!).  Here are some thoughts on
individual classes though:

1. Stat 110: Taught by Joe Blitzstein this is the introduction to
probability.  There is no data in this course so you won't get "practice in
application" but it gives you a much firmer understanding of probability and
the distributions that we assume for the data in generalized linear models.
 I think everyone interested in methods should take this class.

2. Gov 2002: Taught by Adam Glynn and Arthur Spirling.  This class is an
overview of various methods focusing mostly on causal inference and light
Bayesian analysis.  Definitely worth taking if you want to learn more about
causal inference.  As it currently stands its more of a reading seminar than
a practical applications course.

3. Stat 139/239: This class covers linear regression from the statistical
perspective.  Useful if you want to practice what you learned in Gov2000 but
I think you could skip it and go straight to...

4. Stat 149/249: This class covers generalized linear models.  Its the
closest approximation to Gov2001 in the stats department.  You cover a lot
of things traditional to GLMs not covered in this class including the
exponential dispersion family, Fischer scoring and analysis of deviance.  It
also helps you to pick up on nuances in the material you might have missed
the first time around!

5. Stat 220: Bayesian Data Analysis.  When you are ready for serious
Bayesian work this is the course for you.  It helps to already know some
Bayesian statistics going in.

6. Stat 221: Statistical Computing with Edo Airoldi.  If you are going to do
methods seriously: take this class.  It helps cement the practical
logistical issues of Bayesian model estimation, EM, coordinate ascent etc.

7. Econ 2140: Econometric Methods with Guido Imbens.  This is similar to a
Gov2001 type class but taught from the econometric perspective.  Imbens is
great but it helps to have a firm foundation befroe going in.

8. Econ 2142: Time Series with Jim Stock.  If you are interested in doing
Time Series consider taking this course.  Jim Stock is probably the top time
series researcher in the country so its an awesome opportunity.  The Stats
department also offers a time series class but it tends to be geared towards
situations with considerably more data than we typically have (e.g. if a
machine produces a thousand widgets per minute...etc)

9. Sociology 275: Social Network Analysis with Peter Marsden.  This is a
great class for learning about network analysis.

More than anything else the key is to just start reading into different
literatures.  Come to Gov3009 (Research Workshop in Applied Statistics) and
read Political Analysis or other methods journals.  At a certain point you
obviously have to stop taking classes- but once you have Gov2001 and a firm
background in probability theory- you should be able to read into any
literature with enough time.

If you have thoughts on other classes or questions about a specific class,
send it out to the list.  Also feel free to come talk to me during office
hours (I've taken quite a few stats classes here).

Brandon

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