I am hooked on to “Markov Chains” these days and they seem to fascinate me as the applications are in almost every field that I look at. I happened to go over Page Rank algo. From a Markov chain’s perspective, the algo can be summarized in 2 steps Step 1 : Represent a random surfer’s movement as a Markov chain Here N is the total number of pages indexed by Google, Q is a transition matrix( irreducible, a periodic) that captures the transition probability of moving from one page to another , p is the page rank of the pages on the internet and alpha is adjustment factor to take in to consideration the inherent importance of a page.

Real Statistics is not primarily about the Mathematics which underlies it: common sense and scientific judgment are more important. But, there is no excuse for not using the right Mathematics when it is available. - David Williams

Rory Sutherland’s commencement speech

“ Furious activity is no substitute for understanding.” - Williams, H.H

MCMC brilliantly explained by Iain Murray : Markov Chain Monte Carlo