Data Science, Statistics, Analytics, Experiment, Causality.
(source) The most important takeaway is that adding too many predictors can lead to wrong results. Models tuned for predictive performance can lead to incorrect causal inferences. There is a big push against “controlling for everything”. In my previous article about Bayesian statistics, I explained