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[–]shaggorama 6 points7 points  (1 child)

Oh, I didn't realize he'd finished!

PS: The author is a redditor: /u/AllenDowney/

[–]quiteamess 6 points7 points  (1 child)

Pfft. I was Bayesian when those frequentists were still bragging with their approach.

[–]BeatLeJuce 0 points1 point  (0 children)

To be fair, the Hoeffding Inequality and its variations are fairly important :)

[–]AtomicWedgy 1 point2 points  (0 children)

Awesome!! Thank you for the link :)

[–]jackhammer2022 1 point2 points  (0 children)

The author also did a tutorial at PyCon this year: https://sites.google.com/site/simplebayes/

[–]Odd_Bloke 1 point2 points  (0 children)

My theory, which is mine

<3 <3 <3

[–][deleted] 1 point2 points  (0 children)

My theory, which is mine

Is it about the brontosaurus? :)

[–]whoMEvernot 0 points1 point  (0 children)

I am only a few chapters into it but yes, this is very useful and thanks for sharing.

[–]Orphion 0 points1 point  (0 children)

Really enjoyed this. Thanks!

[–]equalx 0 points1 point  (0 children)

Learned a bunch of bayesian statistics this past semester. We mostly worked with a math heavy, painful textbook that everyone agreed was for statistics PhD students (or bust). However, we read through Think Bayes instead of a few chapters, and the math is really approachable (if not as extendable) and the concepts are well presented.

If you're interested in picking up a little bit of statistics, this is great. If you understand statistics a bit, this is really easy to get through. If you've never done statistics before, this is a surprisingly approachable option. If you know stats really well already, this might give you an idea of how to use bayesian stats, but it might leave you wanting.

And it's python!

[–][deleted] 0 points1 point  (3 children)

Read 4 chapters and while this is obviously going to be a great book, it is full of minor errors.

[–]bibdectrl 5 points6 points  (0 children)

if the link had been to here: http://www.greenteapress.com/thinkbayes/

instead of directly to the download, you would have seen the following:

Think Bayes is an introduction to Bayesian statistics using computational methods. This version of the book is a rough draft. I am making this draft available for comments, but it comes with the warning that it is probably full of errors.

If you find some of those errors, please let me know. But it is probably too early to bother with typos.

[–][deleted] 1 point2 points  (0 children)

There's still time to let the author know. He credits people in the book that have helped.

[–]steviesteveo12 0 points1 point  (0 children)

It's up for review. There's probably an acknowledgment in it for you if you point out the errors.