This seems to be the week for us to plug our new books (and I’m eagerly awaiting John and Lynn’s The Gamble), so I thought I’d say a few words about *my* own new book (at the time of this writing, still available at 40% off if you pre-order from Amazon):

The above images represent a Gaussian process decomposition of the time series of number of births in the U.S. as recorded each day from 1969 through 1988. As you can see, births are less likely on the weekends and this trend has been increasing over the years. In addition, kids are most likely to be born in the last summer months, and there are also large effects on particular days, with many fewer babies born on major holidays.

That’s cool but it’s not really political science. What I want to (briefly) discuss here is, what does

Bayesian data analysis have to do with political science? Nowadays “Bayes” is commonly used to denote rational behavior, but that’s not we’re really talking about. We do have one chapter on decision making but most of the book is about learning from data.

In statistics there’s a lot of talk about “Bayesian inference,” but by Bayesian *data analysis* we mean something more. Here are the three steps of Bayesian data analysis:

1. Model building

2. Inference given a model

3. Model checking.

Step 2 is the glamour boy, but steps 1 and 3 are important too. In particular, step 3 is typically achieved using graphics, what is sometimes called “exploratory data analysis.”

Where does “Bayesian” come in? In Bayesian inference, all unknowns are represented by probability distributions. This fits well with a view of the world in which patterns are variable (for example, in which the incumbency advantage is larger for some congressmembers than others) and uncertain (so that we are suitably modest about our forecasts and our claims of general discoveries). At a technical level, Bayesian inference works well when fitting models with large numbers of parameters (such as the varying-intercept, varying-slope regressions that come into play when doing multilevel regression and poststratification). If you want to fit the best ideal-point models and do Mister P, you’ll want to understand Bayes.

What about political science? Bayes should be just as important in sociology or psychology or economics or medical research; these are all areas with large amounts of uncertainty and variation. I just happen to know more about political science than about these other fields. In addition, I have found political scientists to be admirably open in their choice of methods, hence there’s no particular resistance when introducing a new set of tools.

I don’t expect or recommend that political scientists *only* use Bayesian data analysis in their quantitative analyses. Rather, I recommend that they—-you—-become aware (to the best of your technical ability) of how these methods work, so you can use them in cases where they are most appropriate (these situations would include forecasting, multilevel modeling, inference for complex models with many parameters, and settings with weak data).

A link to the full table of contents for our book is here.

Ive no training in political science, (or post grad education)but am looking to begin to get a grasp of stats etc..so I was wondering, since political scientists arent staticians and will have a relatively limited training in stats etc, is there a danger that they might use quite unsophisticated methods which wont tell them a whole lot about the question they’re looking to answer?* Or is there just a set of procedures that most can learn, with the high end theorising and groundbreaking work being done by those actually trained in stats?

(If you see what I mean. I know thats not particularly clear..)

*For example Ive been talking to a few people trained in computer programming who complain about staticians etc not ‘really understading’ computer languages, and so not getting the most of of them

Btw, Im going to buy your book, but being honest is there a need to buy the new edition..I generally go for the newest editions, but is there a big difference btw edt 2 & 3?

Hi–this link describes some differences between the 2nd and 3rd editions. There’s a bunch of new material on more advanced computation and nonparametric models.

Most younger political scientists are quite well trained in statistics, actually. Statistical modeling is used in almost every (non-theory) article published in the top journals and sequences in statistical research methods are a growing requirement in the majority of PhD-granting departments.

Thats what Im trying to get at, is ‘well trained’ enough?

As in, theres a diferrence between being well trained in something, and developing a really deep expertise/understanding..how do you know when your training is enough and theres not a whole lot of nuance youre missing?

That is why we have a peer review process.

I don’t really know what you mean by deep expertise though. At some point that can become counterproductive

Moreover, that nuance you are talking about is probably a little overstated. If you aren’t sure about something, look it up. Furthermore, we are (most of us) in a university setting. If you are unsure about something, look it up or ask one of those “experts” in the stats department (hopefully they will not suggest completely atheoretic statistical models that maximize model fit).

“I don’t really know what you mean by deep expertise though”

I think the problem here might be I dont have a clue what Im talking about : )

I think my question was along the lines of (for example) – if you were looking to specialise in human rights norms, then I guess youd have to know the lit inside out, know the debates, the case studies etc, so know the area perfectly -but do you have to have the same kind of depth of knowledge when doing statistical analysis etc about the methods youre using..but I guess, retrospectively , thats actually a slightly nonsensical way of viewing it : )

You win. I am semi-trained in regression and time-series and have yet to take a class in Bayesian. Yet I know it is important to know and understand. As a 3rd year PhD student- but an old one at age 58 (using GI Bill to fund after U.S. Army career)- I don’t have that much time left to learn everything I want to learn.

I am hoping your book does that- enables me to learn on my own- stumbling thru the chapters- with a minimal amount of throwing the book against the walls.