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What book will teach the most rigorous way the regression analysis? I read as a mathematician myself, and now I have to improve my statistical skills to get a job. I would like to learn what kind of methods there are to measure how to fit model to data and why those methods work. I'm not afraid to work through proofs. Is, for example, "Applied Regression Analysis and Other Multivariable Methods" written by David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam and Keith E. Muller good for learning the subject rigorously? Are there books similar to "Statistical inference" written by Casella and Berger, but concentrated on regression analysis?

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marked as duplicate by kjetil b halvorsen, Michael Chernick, mdewey, Jeremy Miles, Jan Kukacka Jun 12 '18 at 6:19

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    $\begingroup$ Note that if you need skills for a job, rigor isn't necessarily the prime requisite, the analytical skills are, and in my experience the more rigorous books are in some cases substantially less likely than the more applied books to convey the skills required to do well at analyzing data. Rigor is important, but I don't think potential employers will be particularly seeking rigor - they'll be seeking data analysis skills. The ideal would be a book with both some rigor and an ability to convey the necessary skills, but I wouldn't sacrifice the skills you need just to get more rigor. $\endgroup$ – Glen_b Feb 15 '14 at 23:18
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    $\begingroup$ My other advice is 'you must read more than one book'. Get a mix of books pitched at different levels and with different mixes of rigor and applied-level guidance. $\endgroup$ – Glen_b Feb 15 '14 at 23:21
  • $\begingroup$ @Glen_b, great comment, could give us a recommendation? $\endgroup$ – avocado Feb 17 '14 at 14:46
  • $\begingroup$ Similar questions have been asked before. Have a look at stats.stackexchange.com/questions/414/… math.stackexchange.com/questions/735075/… $\endgroup$ – kjetil b halvorsen Jul 9 '14 at 0:09