Science Book Club discussion

Discussion for our Dec 2017 book: The Theory That Would Not Die

I wasn't knowledgeable about Bayes theory before I started the book. The author spends surprisingly little time explaining how it works in the first few chapters before jumping into examples of it's successful application; development of the worker's comp system for example. I was frustrated because I couldn't grasp why or how it was applied, I just couldn't pick up on it. I stopped and googled Bayes theory. There are some pretty good explanations readily available. The concept is actually very intuitive once you're properly introduced, especially to the difference between Bayesian and frequentist reasoning.

I've enjoyed the book a lot more since I did this. I'm just now reading about Turing and the Enigma code and it's fascinating.

I know !! I felt the same frustration. The book jumps into the history and applications of Bayes without some kind of dive into what makes the Bayes theory. A rudimentary explanation would have been good.

Right now reading about Turing and his 'bombes'. So far so good.

However I had expected this book to be more scientific than historic. So far it has only been a narrative. Lets see what the coming chapters hold.

I never saw the highly regarded "The Imitation Game" movie about Turing, but I think I'll check it out. I'm a fan of Benedict Cumberbatch from Sherlock.

I have not seen that movie either. I have seen Benedict Cumberbatch in Sherlock of course !

Just finished. This is the second book in a row for which I wish I would have read the appendixes (appendices?) first.

The first appendix is a humorous comparison of frequentists with Catholics, and Bayesians with Fundamentalists. I thought it was funny and insightful. Theologically, I'm a Catholic. I don't think I'm smart enough to know where I stand as a statistician.

The second appendix is a good explanation of Bayesian application. It starts with an example about mammograms and breast cancer frequency, which seems to be the go-to example people use when explaining Bayesian probabilities, and it follows with some other clear and simple to understand applications.

If you like this book, the author has some lectures on you tube which are interesting. The one I liked best was a presentation at Google.

Still about half way through but now am going to check the appendices based on your experience.

Thanks.

Finished the book. I will admit I was expecting a more scientific book. I would categorize this as historical but it is extensively researched. It was interesting to read the tumultuous history behind the Bayes rule.

Hi guys, The Imitation Game is superb and yes Alan Turing (Cumberbatch), the a little eccentric guy really saved the day by breaking up the code of Enigma, the machine once was the hardest to decode. Take your time and watch the movie, you'll enjoy it.

For something a little more technical check out Probabilistic Robotics or Probabilistic Graphical Models: Principles and Techniques.

I first learned about Bayesian techniques from watching lectures by Sebastian Thrun at coursera and udacity. Actually I first watched the AI class when they were doing a trial run before the existence of coursera and udacity.

Some of the videos can be found on youtube. https://www.youtube.com/playlist?list...

Serendipity?

It seems I notice some reference to Turing every day since since this conversation started. Funny how the mind works.

I thought this was funny, a truly awful version of Jingle Bells by 2017 standards but ground-breaking at the time.

http://www.openculture.com/2017/12/th...

It is similar to adding a new word into one's vocabulary I think. Suddenly that word seems to pop up everywhere before fading. One wonder's how come it was not noticed before - especially when it is so common !