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E-grāmata: Real Estate Analysis in the Information Age: Techniques for Big Data and Statistical Modeling

(University of North Texas, USA), (University of Melbourne, Australia), (Director of Economic Research, Greenfield Advisors, USA),
  • Formāts: 180 pages
  • Izdošanas datums: 09-Nov-2017
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781315311111
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  • Formāts: 180 pages
  • Izdošanas datums: 09-Nov-2017
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781315311111
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The creation, accumulation, and use of copious amounts of data are driving rapid change across a wide variety of industries and academic disciplines. This ‘Big Data’ phenomenon is the result of recent developments in computational technology and improved data gathering techniques that have led to substantial innovation in the collection, storage, management, and analysis of data. Real Estate Analysis in the Information Age: Techniques for Big Data and Statistical Modeling focuses on the real estate discipline, guiding researchers and practitioners alike on the use of data-centric methods and analysis from applied and theoretical perspectives. In it, the authors detail the integration of Big Data into conventional real estate research and analysis. The book is process-oriented, not only describing Big Data and associated methods, but also showing the reader how to use these methods through case studies supported by supplemental online material. The running theme is the construction of efficient, transparent, and reproducible research through the systematic organization and application of data, both traditional and big. The final chapters investigate legal issues, particularly related to those data that are publicly available, and conclude by speculating on the future of Big Data in real estate.
Foreword ix
Edward Coulson
Acknowledgements xi
Abbreviations xii
Contributors xiii
Introduction xv
PART I Data
1(22)
1 Traditional real estate data
3(11)
2 Big data
14(9)
PART II Tools and Processes
23(44)
3 Software tools for real estate analysis
25(11)
4 The analytical workflow
36(11)
5 Gathering real estate data
47(5)
6 Data management
52(7)
7 Data preparation
59(8)
PART III Modeling and analysis
67(74)
8 Exploratory data analysis
69(17)
9 Data cleaning: techniques to deal with outliers, errors, and missing data
86(15)
10 Modeling real estate prices
101(13)
11 Analysis of unstructured text
114(13)
12 Real estate analysis case study
127(14)
PART IV Legal and future
141(18)
13 The legalities of big data
143(12)
Lucy Cradduck
14 The future of big data
155(4)
Index 159
Kimberly Winson-Geideman is Senior Lecturer in Property at the University of Melbourne, Australia.









Andy Krause is Principal Data Scientist at Greenfield Advisors, USA.



Clifford A. Lipscomb is the Vice Chairman and Co-Managing Director at Greenfield Advisors, USA.









Nicholas Evangelopoulos is Professor of Business Analytics at the University of North Texas, USA.