In a previous post we were discussing the pros and cons of parametric and non-parametric models, and how they can complement each other. In this post, we will add a little more into the story. More specifically, we are going to talk about bounds to the probability that a random variable deviates from its expectation. In these … Continue reading Useful rules of thumb for bounding random variables (Part 1)
This post is my interpretation of Chapter 10 of the book "Advanced Data Analysis from an Elementary point of view". It is one of the most interesting reads I have found in quite some time (together with this). Actually, the original title for the post was "Book Chapter review: Using non-parametric models to test parametric model … Continue reading Book Chapter Review: If your model is mis-specified, are you better off?