Teaching Philosophy
How our teaching empowers your success
Many people are looking for an on-ramp into the world of causal inference methodologies and need a clear
sense of direction, as well as an opportunity to get on board at their own pace. My style of teaching uses clear exposition, examples of studies, and metaphors
and stories that can elucidate more abstract ideas. I draw on pop culture, studies in health
as well as economics, discussions of weird natural experiments creating surprising opportunities to
answer elusive questions, and as I said, programming exercises. My classes are paced deliberately slower
because I want students to gain depth and not merely topical knowledge. And so in addition to me
talking, I use coding labs with some assignments and dive into the
programming “in front of them” and with them to show how I think, the kinds of questions I
have, and the decisions I make when writing code. And this has been a considerable success for many
people as testimonies show.
Coding Exercises
Why we focus on coding in our sessions
It is my opinion that many people today learn causal inference, not simply through the calculus and
exposition of the logic of the statistical modeling, but also through step by step walk through exercises using code. Code. Code has become for many of us the lingua
franca of statistics and research, moreso than the heady equations of the underlying models themselves.
To learn either but not the other is to often be substantially handicapped in one’s own work. One must know what something does, why it does, but also, how to do it.
And so my workshops are not merely lessons in statistics. They are also opportunities to code together
in labs.
We will learn to code via implementation of methods, e.g.
regression discontinuity, instrumental variables and difference-in-differences, using R, Stata and
python. But, in the process of learning these designs well in these languages, the accidental
byproduct will be a greater depth of understanding of the languages themselves too. Just like you
often cannot see a star in sky when you stare at it directly, but can when you look just to the left
or the right, so is for many of us the way in which we learn new programming languages.
Mixtape Sessions
The value in attending our workshops
Mastering some field, like causal inference, with its tedious details and subtleties, not to mention the
coding that goes with it, is for many of us simply too time
consuming. In other words, it isn’t that we couldn’t, if we had an infinite amount of time,
master these subjects. It is that we don’t have an infinite amount of time. The value of these workshops
is having an explainer. I use a variety of rhetoric and pedagogies to
do this. Sometimes, I take us through the algebra of some estimator because I know until you see it with
your own eyes you simply will not believe it. And other times, I belabor a point using metaphors,
stories and pictures. There is a role for all these things in explanations. And I grab hold of anything
and everything that I believe can help you have epiphanies, breakthroughs
and most of all success in how you define it.
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