This is an article on causal inference and decision making. There are two parts to this article. The first part introduces causal inference and explains why it is important for decision making. The second part focuses on how to apply causal inference to a real project. Here, I’ll present the four key steps of causal inference, which is an effective framework to structure your analysis end-to-end. You will see a detailed walk-through of the four steps applied to an actual use case. It’s a long post, so grab a coffee and make yourself comfortable!
Mean vs Median Causal Effect
However, sometimes we might be interested in quantities different from the average, such as the median. The median is an alternative measure of central tendency that is more…