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03 01 Part 1 of 1 Generalized Linear Models
Applied Regression Analysis, Linear Models, and Related Methods
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Indeed, I recommend it as a useful learning text and resource for researchers and students in any field that applies regression or linear models that is, most everyone , including courses for undergraduate statistics majors…. The author is to be commended for giving us this book, which I trust will find a wide and enduring readership.
MIT Press, A comprehensive introduction to neural networks and deep learning by leading researchers of this field. Written for two main target audiences: university students undergraduate or graduate learning about machine learning, and software engineers. This is a PDF compilation of online book www. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and Wiley, A new edition of the definitive guide to logistic regression modeling for health science and other applications.