000			01409 a2200193 4500
005			20250128092323.0
020			_a9781493979363
082			_a519.5 KUH
100			_aKuhn, Max.
245			_aApplied predictive Modeling
260			_bSpringer _aNew York _c2013
300			_a600
520			_aThis multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
650			_aMathematical statistics
650			_aMathematical Models
650			_aPrediction Theory
700			_aJohnson, Kjell
942			_cBK _2ddc
999			_c49458 _d49458