## Future Post Machine Learning for Causal Inference: Synthetic Control and Double Machine Learning

** Published:**

This post is inspired by Frank Diebold’s

** Published:**

This post is inspired by Frank Diebold’s

** Published:**

This post compares the way random variables are handled in Julia/MATLAB/R/STATA/Mathematica/Python. It was inspired by Bruce Hansen’s recent textbook which compares statistical commands in Matlab/R/STATA on page 114. This post will focus on the main methods for working with random variables in a language: e.g. Distributions.jl is the flagship Julia package for random variables, MATLAB’s internal distributions, Base R, Base STATA, Mathematica, and Python’s SciPy.

** Published:**

The goal of this post is to illustrate a point made in a recent tweet by Amit Ghandi that Simpson’s Paradox is a special case of omitted variable bias.