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Think Bayes - Bayesian Statistics Made Simple

greenteapress.com

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Re: Think Bayes - Bayesian Statistics Made Simple

#31

Post by gwern »

Fixnum wrote: post #29
dan_yall wrote: post #26

Earlier quoted context omitted.

Free pdf is available here: http://bayes.wustl.edu/etj/prob/book.pdf It's always nice to see good things come out of Wash U. (Alum here.)

Unfortunately, it's only the first 95 pages.

There must be a fuller version floating around, though; my PDF version has 548 pages and ends with Appendix E, 'Multivariate Gaussian Integrals'.

EDIT: In case anyone wants to make me feel bad about pirating, Jaynes is dead, and besides that, I bought a hardcopy as backup.

Re: Think Bayes - Bayesian Statistics Made Simple

#32

Post by AllenDowney »

PostOnce wrote: post #27

I'm a big fan of the author's other books, Think Python and Think Complexity (haven't had the time for Think Stats), I found them more understandable than most other books that purport to teach people of the same skill level. I'm hoping this will be as good, but all the negative comments here leave me skeptical. Perhaps this is the crowd that would enjoy K&R C more than Think Python. The former is more of a reference…

Ignore the haters -- Think Bayes is going to be awesome!

Just kidding (mostly), but your point is correct: there is no book that is right for all audiences. But if you can program, and the mathematical approach to this material doesn't do it for you, this book might.

Re: Think Bayes - Bayesian Statistics Made Simple

#33

Post by AllenDowney »

nowarninglabel wrote: post #30
AllenDowney wrote: post #23

Earlier quoted context omitted.

I am coming around to the conclusion that this example is more trouble than it's worth. I think it's kind of fun, but it does seem to annoy people. This kind of feedback is exactly why I like to post drafts early. Expect this example to magically disappear very soon :)

Wow, great to see a reply from you, and thanks for taking feedback :)

And... it's gone!

I re-read the chapter and decided that example was doing nothing except confusing half the audience and antagonizing the other half.

Re: Think Bayes - Bayesian Statistics Made Simple

#34

Post by Groxx »

>This HTML version of is provided for convenience, but it is not the best format for the book. In particular, some of the symbols are not rendered correctly.

I would actually recommend the opposite - they have ASCII versions of the symbols that e.g. Chrome might not render correctly, and all I checked looked fine. The PDF meanwhile copies this text from the (not linked) link to the "girl named Florida" article:

  ❤tt♣✿✴✴❛❧❧❡♥❞♦✇♥❡②✳❜❧♦❣s♣♦t✳❝♦♠✴✷✵✶✶✴✶✶✴❣✐r❧✲♥❛♠❡❞✲❢❧♦r✐❞❛✲s♦❧✉t✐♦♥s✳❤t♠❧
And the sections are linked in the HTML version, where they are not in the PDF, which seems like a simple oversight (that infects the vast majority of PDFs, sadly).

Re: Think Bayes - Bayesian Statistics Made Simple

#35

Post by Wilduck »

gwern wrote: post #31
Fixnum wrote: post #29

Earlier quoted context omitted.

Unfortunately, it's only the first 95 pages.

There must be a fuller version floating around, though; my PDF version has 548 pages and ends with Appendix E, 'Multivariate Gaussian Integrals'. EDIT: In case anyone wants to make me feel bad about pirating, Jaynes is dead, and besides that, I bought a hardcopy as backup.

I found the full text here:

http://www.naturalthinker.net/trl/texts/Science/Jaynes,%20E....

The first couple pages are a bit funny looking, but after that, there are all 500+ pages. It was the fourth result on Google for me.

Re: Think Bayes - Bayesian Statistics Made Simple

#36

Post by incision »

danso wrote: post #25
ph0rcyas wrote: post #18

Earlier quoted context omitted.

Agree. It is unbelievable - one has to study it to believe it.

Going to Amazon right now... * edit: Doh, no Kindle version. I don't mind paying $90+ for a good book though, just like it to be electronic: http://www.amazon.com/Probability-Theory-The-Logic-Science/d...

Well, it's available on Google Books [1], but I don't know about $63 for what appears to be a skewed scan of the print book.

Personally, I searched out a PDF and based on what I've read so far, I'm itching to pull the trigger on Amazon as I'm simply loving what I'm reading.

1: http://goo.gl/UHMBi

Re: Think Bayes - Bayesian Statistics Made Simple

#37

Post by equark »

AllenDowney wrote: post #22
equark wrote: post #9

My problem with books like this is that they have almost no connection to why Bayesian statistics is successful: Bayesian statistics provides a unified recipe to tackle complex data analysis problems. Arguably the only known unified recipe. The Bayesian book I want should emphasize how Bayes is a recipe for studying complex problems and teach a broad range of model ingredients. Learning Bayesian statistics is about b…

Yes, that's exactly what the objective of this book is! I am not using computation out of necessity, but rather because I think it provides leverage for understanding the concepts, and learning to (as you say) compose traditional models and build new ones. As the book comes along, I am finding that many ideas that are hard to explain and understand mathematically can be very easy to express computationally, especiall…

I'd recommend using as many real examples as possible. Things like forecasting, product recommendations, topic modeling, etc. While you can conceptually explain how Bayesian statistics is a unified recipe, it's incredibly hard to have this sink in with toy problems. This is especially true since many people using traditional tools are actually using advanced methods to solve real problems, so when they start reading about urns or doors it all comes across as rather academic. That's sad because the benefit of Bayesian coherency is mostly that it leads to a highly productive mode of practical data analysis.

Definitely shoot me an email at tristan@senseplatform.com if you're interested in the computational side of this area. At Sense (http://www.senseplatform.com), we're working on making applied Bayesian analysis as amazing as it should be.

Re: Think Bayes - Bayesian Statistics Made Simple

#38

Post by markus2012 »

AllenDowney wrote: post #23
nowarninglabel wrote: post #10

So, I'm going to counter here and say I don't find this to be a good intro. I started reading and had not heard of the "Girl named Florida" problem and then went to the linked to blog post http://allendowney.blogspot.com/2011/11/girl-named-florida-s... The way he explains it I found to be confusing and counter-intuitive. I've taken basic stats in college, and learned some of the associated problems, though not this o…

I am coming around to the conclusion that this example is more trouble than it's worth. I think it's kind of fun, but it does seem to annoy people. This kind of feedback is exactly why I like to post drafts early. Expect this example to magically disappear very soon :)

Underneath Figure 4.2:

I want to addresss on possible source

should be

I want to addresss one possible source

(on -> one)

Peace.

Re: Think Bayes - Bayesian Statistics Made Simple

#39

Post by trhtrsh »

AllenDowney wrote: post #23
nowarninglabel wrote: post #10

So, I'm going to counter here and say I don't find this to be a good intro. I started reading and had not heard of the "Girl named Florida" problem and then went to the linked to blog post http://allendowney.blogspot.com/2011/11/girl-named-florida-s... The way he explains it I found to be confusing and counter-intuitive. I've taken basic stats in college, and learned some of the associated problems, though not this o…

I am coming around to the conclusion that this example is more trouble than it's worth. I think it's kind of fun, but it does seem to annoy people. This kind of feedback is exactly why I like to post drafts early. Expect this example to magically disappear very soon :)

The problem with the Girl Named Florida is that the ambiguous wording is more confusing than the math.

Ambiguous: "In a family with two children, what are the chances, if one of the children is a girl named Florida, that both children are girls?"

More clear, and emphasizing the importance of precise wording when discussing probability: "Among families with two children, with at least one of the children being a girl named Florida, what portion have two girls? (Assume that all names are chosen randomly from the same distribution, independently of all other factors; and sex is determined as by a fair coin toss.)"

Re: Think Bayes - Bayesian Statistics Made Simple

#40

Post by trhtrsh »

pmjordan wrote: post #20

So this is all very well and good, I've had about 5 intros to Bayesian Statistics. But those are a fair bit away from actually applying that knowledge in practice in software. Let's say we have N different kinds of events with unknown probabilities and unknown dependence or independence between them. The naive approach to gathering data on the probability of event n occurring following an occurrence of event m would…

I think the general approach is dimensionality reduction: start measuring, and round down to 0 for the low-correlation pairs of events.

Do you actually have a stream of more than N^2 observations to process? If not, then most of your correlations are in fact 0, and sparse-matrix techniques apply.

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