Welcome to class!

getting started

Monday January 9, 2023 at 2:01 PM

Hello everyone!

I’m Andrew Heiss, your professor for PMAP 8521 (Evaluation Research) this spring, and I’m so excited for the class! In this class you’ll learn all about causal inference, or how to legally claim causation with statistics. In your past stats courses you were always taught “correlation isn’t causation,” which is mostly true, except when it’s not. In this class you’ll get to legitimately make causal claims.

We’ll cover fun tools like directed acyclic graphs (DAGs), randomized controlled trials, difference-in-differences analysis, regression discontinuity analysis, and instrumental variables. You’ll also learn the statistical language R, which is free (which means you can keep using it after you graduate and not have to pay for really really expensive SPSS or Stata licenses). I’ve had former students get jobs because of the R part of this class—tons of organizations are looking for R skills nowadays.

I have a few important announcements before class:

Quick background about me: I’m an assistant professor here at the Andrew Young School, where I’ve been teaching MPA/MPP microeconomics, program evaluation, and data visualization. I moved here from Utah in 2019, where I was a visiting professor of public management at the Marriott School of Business at Brigham Young University (BYU). While at BYU, I taught microeconomics, statistics, and data visualization (basically the same stuff I’m teaching now). I finished my PhD in public policy and political science from Duke in 2017, and before then I finished my MPA in nonprofit management from BYU in 2012.

When I’m not teaching stats and evaluation, I research international nonprofits and political science. And when I’m not teaching or researching, I’m normally chilling at home with my 6 (!!) kids (see https://www.heissatopia.com/ for photos and hilarious stories).

Again, I’m really excited to get started next week. This spring semester should be a blast!