Spatial regression models /

By:

Michael Don Ward [Author]

Material type: Text

TextPublication details: Los Angeles, Calif. : Sage, 2019.Edition: Second editionDescription: 112 pages; 1 online resourceISBN:

9781544328836

Subject(s):

DDC classification:

REF 519.5 W21

Summary: NEW TO THIS EDITION: New material on making and using maps as a method of displaying and collecting data is included. Updated material that deals with a wider range of straightforward spatial models, including those which combine time and spatial dependence has been incorporated. All of the literature and examples have been updated. Code is now hosted on the author created online repository, along with data and other materials. KEY FEATURES: This book assumes no prior knowledge and is geared toward social science readers, unlike other volumes on this topic. The text illustrates concepts using well known international, comparative, and national examples of spatial regression analysis. Each example is presented alongside relevant data and code, which is also available on an online repository maintained by the authors

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Item type	Current library	Call number	Status	Date due	Barcode
REFERENCE BOOKS	LAPULAPU-CEBU INTERNATIONAL COLLEGE REFERENCE SECTION	REF 519.5 W21 2019 (Browse shelf(Opens below))	Available		002707

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Previous	REF 519.5 P33 Statistics : learning from data /	REF 519.5 R86 Statistics workbook /	REF 519.5 R86 2019 Statistics essentials for dummies /	REF 519.5 W21 2019 Spatial regression models /	REF 519.50243 Es74 Essentials of statistics for the behavioral sciences /	REF 519.50243 Es74 2021 Essentials of statistics for the behavioral sciences /	REF 519.502855133 H32 R companion to elementary applied statistics /	Next

NEW TO THIS EDITION: New material on making and using maps as a method of displaying and collecting data is included. Updated material that deals with a wider range of straightforward spatial models, including those which combine time and spatial dependence has been incorporated. All of the literature and examples have been updated. Code is now hosted on the author created online repository, along with data and other materials. KEY FEATURES: This book assumes no prior knowledge and is geared toward social science readers, unlike other volumes on this topic. The text illustrates concepts using well known international, comparative, and national examples of spatial regression analysis. Each example is presented alongside relevant data and code, which is also available on an online repository maintained by the authors

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