Data Science, Analytics, Causal Inference, Editors Pick.
Source: https://www.pexels.com/photo/paper-on-gray-laptop-669617/ In Part 1, we looked at how to use Causal Inference to draw the right conclusions — or at least not jump to the wrong conclusions — from observational data. We saw that confounders are often the reason why we draw the wrong