Doing Bayesian Data Analysis at Jacob Bernoulli's grave

The book visited the grave of Jacob Bernoulli (1655-1705) in Basel, Switzerland, as shown in these photos taken by Dr. Benjamin Scheibehenne. Jacob Bernoulli pre-dated Bayes (1701-1761), of course, but Bernoulli established foundational concepts and theorems of probability.

The cutie admiring the book in the first photo is Benjamin's daughter. Many thanks to Benjamin and family for venturing out to take these photos. Thanks also to Benjamin and colleagues for hosting my visit to Basel for a day back in June, during which we unfortunately did not have time to visit Jacob Bernoulli's grave.

If you find this amusing, you might also like the book at Bayes' tomb and the book at R. A. Fisher's remains.

The Book Visits Fisher

On their recent visit to St. Peter's Cathedral in Adelaide, colleagues Dan Navarro and Amy Perfors posed the book at the site of R. A. Fisher's remains. What is the probability of this happening if the null hypothesis were true?

Many thanks to Dan and Amy!
And see the book at Bayes' tomb, too.

Why the puppies?

The posterior distribution is a compromise between the likelihood and the prior: The half-up ears are a compromise between the perky ears and the floppy ears. The marginal likelihood, a.k.a. evidence, is not needed in MCMC methods, so it gets sleepy with nothing much to do.

If the puppies bother you, a solution can be found at this other blog post.

The Book visits Bayes

On his recent visit to Bunhill Fields, Mark Andrews snapped a photo of the book at Bayes' tomb:

Many thanks to Mark!
And see the book at Fisher's remains, too.

Jocular Disbelief

Posted by Yann LeCun  -  Jan 19, 2012  -  Public Google+

Joke of the day (true story, circa 2004):
Radford Neal (giving a talk): I don't necessarily think that the Bayesian method is the best thing to do in all cases...
Geoff Hinton: Sorry Radford, my prior probability for you saying this is zero, so I couldn't hear what you said.

Court outlaws Bayes' rule!

Image from the article in The Guardian

Well, sort of. From this brief article in The Guardian (UK), it seems that the judge was most concerned about dubious values for the probabilities being used for the terms in Bayes' rule, not the validity of Bayes' rule itself. The judge seems to have been worried that garbage in yields garbage out. But the article also gives the impression that the judge outlawed the use of Bayes' rule in court, unless the component probabilities could be proven. That's like outlawing the use of modus ponens, unless the antecedent can be proven.

Maligned Puppies! (Review in Journal of Economic Psychology)

In a recent review of the book in the Journal of Economic Psychology*, Dan Goldstein perspicaciously says 

"A person would have to make an effort not to learn this material after following this tutorial. The book is relentlessly clear. Topics are explained analytically as well as visually and code is provided with which the reader can see and change every assumption made." 

Despite this brilliant and insightful assessment, Dan later states "The cover has puppies on it. Yes, puppies. Had paper grocery bags not disappeared from supermarkets, I would have covered my copy to avoid the strange looks my thoroughly quantitative colleagues gave me as I spent weeks working through the book."  

Well, the solution to this problem is just a Post-It away! See photo at right.

Thank you, Dan, for working through the book and writing such a thoughtful review.

P.S. As explained at this other blog entry, the happy puppies are named Prior, Likelihood, and Posterior. The Posterior puppy has half-up ears, a compromise between the perky ears of the Likelihood puppy and the floppy ears of the Prior 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.)

* Goldstein, D. G. (2011). Book review. Doing Bayesian Data Analysis: A Tutorial with R and BUGS, John K. Kruschke. Academic Press, Elsevier (2011). ISBN-13: 9780123814852. Journal of Economic Psychology, 32(5), 724-725. doi:10.1016/j.joep.2011.05.010

Horses, donkies, and mules

This anti-Bayesian joke is floating around various sites on the internet:

"A Bayesian is one who, vaguely expecting a horse, and catching a glimpse of a donkey, strongly believes he has seen a mule."

In that case, everyone is a Bayesian. Researchers in perceptual science have shown over and over that background knowledge and expectation can strongly influence perception, especially when the visual stimulus is unclear. Anecdotal cases of this abound; e.g., the 1950s TV show in which people say (roughly) "Look, up in the sky, it's a bird, no, it's a plane, no, it's Superman!" Their prior knowledge indicates that flying things should be birds or airplanes, and it's only with accumulating visual data that the prior is overwhelmed.

And there is an error in the joke. If an actual Bayesian vaguely expects a horse and catches only a glimpse of a donkey, then s/he believes s/he has seen a mule only with great uncertainty, not strongly.

A Bayesian and a frequentist are out for a drive...

Photo by Cary Wolinsky

A Bayesian and a frequentist are out for a springtime drive in the country. The Bayesian notices a flock of sheep on the hillside, and says, "Look, the sheep have been shorn." The frequentist replies: "Well, on the sides facing us!"

[Meaning: The Bayesian is using prior knowledge to infer that the sides of the sheep away from the viewer have also been shorn, but the frequentist refuses to use prior knowledge.]