I've written previously about using the Bonferroni correction for the multiple comparisons problem. While it is without a doubt the simplest way to correct for multiple comparisons, it is not the only way. In this post, I discuss Scheffé's method for constructing simultaneous confidence intervals on arbitrarily many functions of the model parameters.
My masters degree focused on Machine Learning, but when I got my first job as a data scientist, I quickly realized there was a lot I still needed to learn about Statistics. Since then I have come to appreciate the nuanced differences between Statistics and Machine Learning and I'm convinced they have a lot to offer one another!
Generalized Additive Models in Python