The Art of Regression Modeling in Road Safety

This unique book explains how to fashion useful regression models from commonly available data to erect models essential for evidence-based road safety management and research. Composed from techniques and best practices presented over many years of lectures and workshops, The Art of Regression Mode...

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Bibliographic Details
Published in:Springer eBooks
Main Author: Hauer, Ezra (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
Subjects:
Online Access:http://dx.doi.org/10.1007/978-3-319-12529-9
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Description
Summary:This unique book explains how to fashion useful regression models from commonly available data to erect models essential for evidence-based road safety management and research. Composed from techniques and best practices presented over many years of lectures and workshops, The Art of Regression Modeling in Road Safety illustrates that fruitful modeling cannot be done without substantive knowledge about the modeled phenomenon. Class-tested in courses and workshops across North America, the book is ideal for professionals, researchers, university professors, and graduate students with an interest in, or responsibilities related to, road safety. This book also: · Presents for the first time a powerful analytical tool for road safety researchers and practitioners · Includes problems and solutions in each chapter as well as data and spreadsheets for running models and PowerPoint presentation slides · Features pedagogy well-suited for graduate courses and workshops including problems, solutions, and PowerPoint presentations · Equips readers to perform all analyses on a spreadsheet without requiring mastery of complex and costly software · Emphasizes understanding without esoteric mathematics · Makes assumptions visible and explains their role and consequences.
Physical Description:XVII, 231 p. 116 illus., 112 illus. in color. online resource.
ISBN:9783319125299