Carlin Et Al: Fill & Download for Free

I love this quote from the beginning of Bayesian Data Analysis by Gelman et al (Amazon.com: Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) (9781439840955): Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin: Books), the leading textbook on applied Bayesian statistics:The process of Bayesian data analysis can be idealized by dividing it into the following three steps:1. Setting up a full probability model—a joint probability distribution for all observable and unobservable quantities in a problem. The model should be consistent with knowledge about the underlying scientific problem and the data collection process.2. Conditioning on observed data: calculating and interpreting the appropriate posterior distribution—the conditional probability distribution of the unobserved quantities of ultimate interest, given the observed data.3. Evaluating the fit of the model and the implications of the resulting posterior distribution: how well does the model fit the data, are the substantive conclusions reasonable, and how sensitive are the results to the modeling assumptions in step 1? In response, one can alter or expand the model and repeat the three steps.In that sense, I think a better term for the subject would be full probability modeling rather than Bayesian statistics. The basic idea is to create a full model for all the relevant quantities, then do the relevant conditional probability calculations (often using Bayes' rule) to quantify our uncertainty about the unknown quantities of interest, given the observed data.The details about how to set up, use, and validate the full probability model is a huge and growing subject, not easily explained in a few words or a few lectures. As references, I recommend Bayesian Data Analysis and, at a more basic level, Amazon.com: A First Course in Bayesian Statistical Methods (Springer Texts in Statistics) (9780387922997): Peter D. Hoff: Books and the free online booksThink BayesandCamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers.

On stage, if you are a good comedian.George Carlin, Chris Rock, Louis CK, et al. have done some great stand-up acts on the subject of race.

Well, as much as I love Louis CK, I'll have to go out on a limb here and say that George Carlin is better.Don't get me wrong, of course Louis CK is one of the best contemporary stand-up comedian, out there, of course, but maybe if he continues doing so, and comes up with bestselling books he may come close to George Carlin.Louis' jokes are good, funny and in sync with the present times. But if you listen closely, it is at best funny and at worst tedious. By tedious, I mean his major chunk of jokes spawn from masturbation, divorce and over-eating. I admit his "Oh my God" set was freaking awesome, but like I mentioned earlier he needs to be consistent, and after watching Louie, I think he will be.George Carlin's jokes were profound, realistic, awe-inspiring, eclectic and very rarely outright offensive. Louis tends to be offensive at times (although I don't take offence, but many people do). If you compare Louis with the present stand-up comedians like Jesselnik, Russel Peters, Aziz Ansari, Dylan Moran, Doug Stanhope et al. he owns them all. Patton Oswalt and Demetri Martin come close to Louis' level,but they lack consistency.I rest my case:P.S: This answer isn't completed, I wanted to expound further on so many aspects, and do justice to the question that had once occurred to me as well, but I gotta hit the sack, exams beckon.