Spatial Regression Models for the Social Sciences : Advanced Quantitative Techniques in the Social Sciences - Guangqing Chi

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Spatial Regression Models for the Social Sciences

By: Guangqing Chi, Jun Zhu

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Hardcover | 5 April 2019

At a Glance

Hardcover
272 Pages

Dimensions(cm)
18.5 x 26.5 x 1.8

Hardcover

RRP $233.00

$229.99

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Providing comprehensive coverage of spatial regression methods, this text explains what each method is and when and how to apply it, connecting concepts to social science research topics. Avoiding mathematical formulas and symbols as much as possible, the book introduces the methods in an easy-to-follow manner, providing comprehensive coverage and using the same social science example throughout to demonstrate the applications of each method and what the results can tell us.

Industry Reviews

"This is an important book bringing together a family of related statistical measures and explaining them in a coherent way. Written by leading researchers in the field, it uses a consistent spatial example and applies and explains various measures within a unifying frame to aid in understanding by readers. As real-time spatial data becomes increasingly prevalent, the need for analysts to accurately and meaningfully interpret this data is rapidly growing." -- David Levinson "The field of spatial regression has grown rapidly over the last decade. This book goes a long way toward filling a gap by providing students and practitioners with a useful text that is written at a level that should make it broadly accessible." -- Peter Rogerson "This is an exceptionally well-written text on spatial data analysis tailored for social science research. It deals with spatial thinking and regression analysis with remarkable depth and expertise in a comprehensive and easy-to-follow manner. It is a primer that should be on every social scientist's shelf." -- Zudi Lu "This introductory book offers a full overview of the different ways in which a standard linear regression model can be extended to contain spatial effects." -- J. Paul Elhorst "Spatial data science is an evolving field. This is a valuable book that introduces to students, researchers, and faculty the foundation of spatial statistics and offers tremendous insights on how to statistically analyze geo-spatial data. Anyone working geo-data must read this book if they want accurate and unbiased research findings." -- J.S. Onesimo Sandoval the book's main strength is its efficiency, organization, and methodical approach to explaining many concepts in spatial regression. It does not necessarily progress in concept difficulty nor in concept importance, but mixes both to form a coherent volume that is a strong reference for both looking up terms as a "refresher" and as a guide to diversifying one's own spatial regression techniques for a comparative analysis -- Clio Andris * EPB: Urban Analytics and City Science *

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