[SciPy-user] Some mathematics/statisctics books

David Cournapeau david@ar.media.kyoto-u.ac...
Wed Jun 11 03:03:32 CDT 2008


didier rano wrote:
> Wahh so many books to read.
>
> But to analysis graph related to time-series, I don't know if I need 
> more a statistic approach or pure mathematic approach. Maybe that I 
> could use both approaches.

It really depends on what you mean by pure mathematic approach. Purely 
mathematic approach to probabilities and statistics are mostly just 
that: purely mathematical. Don't get me wrong, maths is great, and 
probabilities/statistics are interesting mathematics topics on their 
own, but if you want to handle graphs, time series and all that, I don't 
think it will help you much.

I second the book by Wasserman, although it does not treat a lot of time 
series stuff. But it is concise and precise (it is written with a 
relatively practical POV by someone who is definitely familiar with the 
theory; in particular, there are a lot of subtle examples and counter 
examples which are well explained, contrary to many other books).

Another book. which I have not read entirely yet, but looks related to 
what you are looking for, is the book by Gelman et al.:

"Bayesian Data Analysis", by Gelman A., John B. Carlin 
<http://www.rch.org.au/cebu/staff.cfm?doc_id=5690>, Hal S. Stern 
<http://www.ics.uci.edu/%7Esternh/>, and Donald B. Rubin.
http://www.stat.columbia.edu/~gelman/book/

Not much theory there, but is really oriented toward data analysis as 
the title suggests :)
>
> Thanks for all your help, and sorry for my poor background in 
> mathematics (I need to learn linear algebre too !)

If you do multivariate analysis, you need to be more than familiar with 
linear algebra, I think. I don't know any good reference on this, but 
some open courseware may be nice (they have some video, too):

http://ocw.mit.edu/OcwWeb/Mathematics/index.htm

cheers,

David


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