Peter Westfall, Andrea L. Arias
Chapman and Hall/CRC
June 11, 2020 Forthcoming
Textbook - 480 Pages - 173 B/W Illustrations
ISBN 9780367458522 - CAT# 355767
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This book unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks and decision trees under a common umbrella; namely, the conditional distribution model. It explains why the conditional distribution model is the correct model, and it also explains (proves) why the assumptions of the classical regression model are wrong. Unlike other regression books, this one takes a realistic approach from the outset that all models are just approximations. Hence, the emphasis is to model Nature’s processes realistically, rather than to assume (incorrectly) that Nature works in particular, constrained ways.
Key features of the book include:
This book has a strong orientation towards science in general, as well as end-of chapter and self-study questions, so it can be used as a textbook for research-oriented students in the social, biological and medical, and physical and engineering sciences. As well, its mathematical emphasis makes it ideal for a text in mathematics and statistics courses. With its numerous worked examples, it is also ideally suited to be a reference book for all scientists.
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