Data science

If You're Going to Learn R, Learn the Tidyverse

This is an opinionated post based on how I teach my undergraduate econometrics course. It will not be for everybody. The title applies mostly to anyone who wants to do data science or econometrics with R. This is the second time I have taught this course with R, and I have changed it around in many ways that I think optimize the process for students. In this post, I’ll cover just two major changes:

Econometrics, Data Science, and Causal Inference

This summer, I am overhauling my econometrics class in many ways, in part because I was pleased to recieve a teaching grant from my college to make more R resources for my econometrics class. Last Fall was the first time I had taught it using R, and I’ve learned a ton since then. Expect a flurry of posts in the coming weeks more on those topics. This post, however, explores some of the trends that I have been thinking about in teaching econometrics, and something monotonous that I have been struggling with that encapsulates the tension in these trends: what to name my course.