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I was recently exposed to some statistical hypothesis testing methods (e.g. Friedman test) at work, and I would like to increase my knowledge on the topic.

Can you suggest a good introduction to statistical significance / statistical hypothesis testing for a computer scientist?

I am thinking of a PDF book or similar, but any other kind of help is welcome.

Edit: I've already found this website but I was looking preferably for some which is easily printable.

Thank you
Tunnuz

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+1 I am interested too in an introduction to hypothesis testing. I have read "Introduction to Statistical Thought" by Michael Lavine math.umass.edu/~lavine/Book/book.html and found it interesting but it does not cover a lot the subject. –  Alessandro Jun 29 '11 at 17:21

3 Answers 3

up vote 4 down vote accepted

http://greenteapress.com/thinkstats/ This seems like it would be useful for you.

Full disclosure: I have not read it, but I am working my way through the Think Like a Computer Scientist in Java, and am finding that extremely useful.

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Great answer, I had already downloaded it, but didn't get through the table of contents, and actually a chapter about hypothesis testing is there for me! –  tunnuz Apr 14 '11 at 12:36
    
However, the book is not covering the topic very widely. –  tunnuz Apr 14 '11 at 13:39
    
@tunnuz - how do you mean not very widely? It seems to cover the basics, and if you grasp all of the material within, you should be well able to move on to more advanced topics. –  richiemorrisroe Apr 14 '11 at 15:26

By far the best I think:

Design of Experiments, Statistical Principles of Research Design and Analysis, 2nd Ed, by Robert O. Kuehl

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Please expand upon this recommendation. Either why you feel it is appropriate or why is is better than some of the other recommendations. –  Andy W Dec 19 '11 at 18:36

I have found a decent introduction in "STATISTICS: AN INTRODUCTION USING R" by Michael J. Crawley.

There is a site where you can download pdfs http://www.bio.ic.ac.uk/research/crawley/statistics/exercises.htm

in particular http://www.bio.ic.ac.uk/research/crawley/statistics/exercises/R3Statistics.pdf explains t test and Wilcoxon test.

But I am still looking for a better introduction...

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