Bayesian Probability In the Day of Covid-19 (via NY Times)

Siobhan Roberts mathplains Bayesian analysis in the age of covid for NY Times readers:

https://www.nytimes.com/2020/08/04/science/coronavirus-bayes-statistics-math.html?smid=tw-share

Bye Bye Bayes…

                                           

One tidbit I found especially interesting/surprising (and had never heard about) from David Spiegelhalter’s current “The Art of Statistics” volume, is that Bayes' Theorem or Bayesian inference/reasoning has been banned in British courts… yeah, you read that right Nate Silver, BANNED in court! ;)  As if statistics weren’t confused and misused enough by lawyers, one of the most common and vaunted modern approaches to probability isn’t even allowed, and this decision goes back at least 8 years.

Here are a few of the links that talk about the decision:

https://www.theguardian.com/law/2011/oct/02/formula-justice-bayes-theorem-miscarriage

https://blog.richmond.edu/physicsbunn/2013/02/28/bayes-banned-in-britain/

https://telescoper.wordpress.com/2013/02/28/bayes-in-the-dock-again/

If any of our friends from across the pond can tell us more about how much controversy or debate this prohibition has produced in UK (or is it 'settled law' at this point?) I’d be curious to hear.

P(B|E) = P(B) X P(E|B) / P(E)

John Horgan took a good whack yesterday at explaining much-heralded Bayes Theorem (includes several good links, and be sure to read the comments section as well):

http://blogs.scientificamerican.com/cross-check/bayes-s-theorem-what-s-the-big-deal/

Bayes-mania

Seeing an awful lot written on Bayesian ideas in the last year (and week!).
Jason Rosenhouse uses the Monty Hall problem and a NY Times article as a launching point for a discussion of the subtlety of Bayes here:

http://scienceblogs.com/evolutionblog/2014/10/01/a-poor-description-of-the-monty-hall-problem/

Rosenhouse takes the Times' article to task, and ends simply with:

"Applying statistics correctly is hard, even for people with professional training in the subject. But the problems are found in the complexity of real-life situations, and not in the underlying philosophical approaches to probability and statistics."

(Rosenhouse's 2009 book on the The Monty Hall problem is great, by the way, if you've never read it -- yes, an entire volume on that one problem)

Meanwhile, The Guardian also presented Bayesian statistics this week: http://tinyurl.com/ojjazs4

And in other statistics briefs, Jeff Leek tries to come to the defense of much-maligned p-values here:
http://simplystatistics.org/2014/09/30/you-think-p-values-are-bad-i-say-show-me-the-data/ 

Ignore Bayes At Your Peril

...are you listening, Karl Rove?

Thanks to the success of Nate Silver in projecting the U.S. Presidential election results, Bayesian statistics have been getting a lot of internet play of late. Bayes' Theorem "bridges the gap between probability and logic" by looking at events not solely in terms of randomness, but in terms of updated known information that can be factored in (probability becomes "conditional" instead of simply random). The idea is simple though the actual application can get rather technical. Here's a basic introductory post to the subject from Grey Matters blog (which includes several additional links and videos):

http://headinside.blogspot.com/2012/11/bayes-theorem.html

Plenty more on Bayes' Theorem from a Google search:

http://tinyurl.com/bbqns46

...and on YouTube as well:

http://tinyurl.com/b2333sr

...And just today 'Mind Your Decisions' blog posted about a simple medical diagnosis problem, which hints at the potential pitfalls of a purely "frequentist" (non-Bayesian) approach to statistics:

http://tinyurl.com/b7nzzn9 

The Bayesian History of Google Cars

Bayes rules....

Short Scientific American blurb from the author of a new book on the work of Thomas Bayes:

http://www.scientificamerican.com/article.cfm?id=why-bayes-rules