Basic Statistics with Sympathy – Part 4: Building arbitrary RNGs in Sympathy

Remember your friend from our very first post? . Well, I am sorry to say that he never really reached French Guyana. He ended up in Carcass, one of the Malvinas/Falkland islands. And his boat was (peacefully) captured by overly friendly pirate penguins. Now he spends his days counting penguins and sheep. He did keep a coin and … Continue reading Basic Statistics with Sympathy – Part 4: Building arbitrary RNGs in Sympathy

Useful rules of thumb for bounding random variables (Part 2)

In the previous post  we looked at Chebyshev's, Markov's and Chernoff's expressions for bounding (under certain conditions) the divergence of a random variable from its expectation. Particularly, we saw that the Chernoff bound was a tighter bound for the expectation, as long as your random variable was modeled as sum of independent Poisson trials. In … Continue reading Useful rules of thumb for bounding random variables (Part 2)

Book Chapter Review: If your model is mis-specified, are you better off?

https://stocksnap.io/photo/HN6OJPDCXD

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?

Basic Statistics with Sympathy – Part 2: Plotting and using the Calculator Node for common functions.

Allow me to introduce you to your new best friend from Sympathy 1.2.x: The improved calculator node. The node takes a list of tables, from which you can establish a new signal with the output for a calculation. There is already a menu with the most popular calculations and a list of signals from the … Continue reading Basic Statistics with Sympathy – Part 2: Plotting and using the Calculator Node for common functions.