[ Firstly, something about the puppies on the cover pages. The happy puppies are named Prior, Likelihood, and Posterior. Notice that the Posterior puppy has half-up ears, a compromise between the perky ears of the Prior puppy and the floppy ears of the Likelihood puppy. The puppy on the back cover is named Evidence. MCMC methods make it unnecessary to explicitly compute the evidence, so that puppy gets sleepy with nothing much to do.

A prediction for tech adoption in Indian markets via Celent: Years ago, I read in John Naisbitt’s book that technology does not change as fast as you want / you predict. In fact things that we expect to happen always happen more slowly . The author shows a ton of examples to show how people were gung-ho about something but eventually it took years to pan out. In the case of HFT prediction too, I think the above time line is a overly optimistic estimate.

In most of the universities in India , statistics curriculum followed at undergraduate and graduate level, is completely outdated. The content taught, is relevant to times where there were: No computational capabilities - All computations had to be performed with paper and pencil. No graphing capabilities - Either All graphs had to be generated with pencil, paper, and a ruler. (And complicated graphs—such as those requiring prior transformations or calculations using the

This book by Michael Lewis delves in to the reasons behind the mysterious success of Oakland Athletics, one of the poorest teams in US baseball league . In a game where players are bought at unbelievable prices , where winning / losing is a matter of who’s got the bigger financial muscle, Oakland A’s go on to make a baseball history with rejected players and rookie players . “Is their winning streak a result of random luck OR Is there a secret behind their winning streak ?