On 27 May 2003 at 17:20, Simon, Steve, PhD wrote: I will only add this: One good book to get an overview of large part of statistics, and which can be used with the free statistical environment R mentioned by Steve Simon, is:
"Modern Applied Statistics with S" by W N Venables and B D Ripley. And when you want to dig deeper into something you find in that book, use their literature list as a guide. I am buying books for our library, and use that literature list as a proof of quality. Warning: This is bad advice if you are frightened by high school algebra. At least expect to refresh your linear algebra. Kjetil Halvorsen > Czwang writes: > > > Can any one here suggest a good set of self-study statistics > > books for a computing scientist with only elementary > > probability and statistics knowledge (one undergraduate course 12 > > years ago) so that he could master the book "The Elements of > > Statistical Learning"? or better, he could become a data miner using > > statistics learning methods. Thanks in advance. --czwang > > You would need a lot of work to become good at data mining. I assume that > getting a masters degree in Statistics is out of the question. Too bad. > That's the sort of background you would need in order to understand the > basic principles of data mining. > > If you had to start somewhere, you should look for good books on linear > regression analysis, logistic regression analysis, and multivariate > analysis. These topic areas are so broad that it is difficult to specify > what the best self-learning books would be. Also, it's hard to know what > book to recommend without knowing your tolerance for mathematical details. > The sorts of books that work well for someone comfortable with multivariable > calculus are quite different from the books that work well for someone who > is frightened by high school algebra. > > You probably also need to learn a good software package. R is an excellent > open source package, and its object-oriented approach will be a natural for > someone with your background. > > If you plan to program these data mining algorithms yourself, then invest in > a good book on statistical computing. > > You might try searching the archives of sci.stat.edu and other newsgroups > for textbook recommendations in some or all of the above areas. > > It won't be easy. This is not something you will be qualified for after > reading one or two books. But if you do decide to follow this career path, > it should be quite interesting and exciting. There's a lot of demand for > data analysis skills and the work is far more engaging than most programming > jobs, in my humble opinion. > > Steve Simon, [EMAIL PROTECTED], Standard Disclaimer. > The STATS web page has moved to > http://www.childrens-mercy.org/stats. > > . > . > ================================================================= > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at: > . http://jse.stat.ncsu.edu/ . > ================================================================= . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
