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Unfortunately my favorites are a bit on the mathy side, so you may want wait for other commenters with better advice. But, there are two books I really feel sh
by jmount 17y ago
Unfortunately my favorites are a bit on the mathy side, so you may want wait for other commenters with better advice. But, there are two books I really feel should not be missed. For statistics: "Statistics, Third Edition" David Freedman, Robert Pisani, Roger Purves. For machine learning: "The Elements of Statistical Learning" Trevor Hastie, Robert Tibshirani and Jerome Friedman.
- jaf656s 17y agofyi, The Elements of Statistical Learning can be found here as a free pdf http://www-stat.stanford.edu/~tibs/ElemStatLearn/ http://www-stat.stanford.edu/~tibs/ElemStatLearn/
- joebottherobot 17y agothere's also an R package with the book's material: http://cran.r-project.org/web/packages/ElemStatLearn/index.html http://cran.r-project.org/web/packages/ElemStatLearn/index.h...
- marcusbooster 17y agoThe Berkeley webcast* Introduction to Statistics, uses "Statistics, Fourth Edition" by Freeman. I don't know what the differences are, but I think it's mostly for the exercises involved. * http://webcast.berkeley.edu/course_details_new.php?seriesid=2009-D-87303 http://webcast.berkeley.edu/course_details_new.php?seriesid=...
- jmount 17y agoI messed up. Statistics 4th edition is the current edition (the one to get), in this case there is no content related reason to deliberately seek out the older edition.
- jmount 17y agoMake that 4th edition (sorry about the mistake).