Essentials of Modeling and Analytics

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A01=Adi Raz
A01=Daniel M. Downs
A01=David B. Speights
Adi Raz
Author_Adi Raz
Author_Daniel M. Downs
Author_David B. Speights
Business Case
Category=JW
Category=KJM
Category=KNP
Daniel M. Downs
Detection
EAS Tag
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Fraud
Internal Theft
Loss Prevention
Loss Prevention Initiative
Loss Prevention Managers
Loss Prevention Professionals
Loss Prevention Programs
Loss Prevention Solution
Loss Prevention Strategies
Loss Prevention Team
Loss Prevention Tools
Multiple Linear Regression
National Retail Security Survey
Organized Retail Crime
Predictive modeling
Random Forest Regression Model
Regression Model
Retail
Retail Loss
Retail Loss Prevention
SARA Process
SAS Code
SAS Output
Scatter Plot
Shrink modeling
Simple Logistic Regression Model
Situational Crime Prevention
Theft

Product details

  • ISBN 9780367878801
  • Weight: 707g
  • Dimensions: 178 x 254mm
  • Publication Date: 12 Dec 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Essentials of Modeling and Analytics illustrates how and why analytics can be used effectively by loss prevention staff. The book offers an in-depth overview of analytics, first illustrating how analytics are used to solve business problems, then exploring the tools and training that staff will need in order to engage solutions. The text also covers big data analytical tools and discusses if and when they are right for retail loss prevention professionals, and illustrates how to use analytics to test the effectiveness of loss prevention initiatives. Ideal for loss prevention personnel on all levels, this book can also be used for loss prevention analytics courses. Essentials of Modeling and Analytics was named one of the best Analytics books of all time by BookAuthority, one of the world's leading independent sites for nonfiction book recommendations.

David B. Speights, Ph.D., is the Chief Data Scientist for Appriss, which provides proprietary data and analytics solutions to address risk, fraud, security, safety, health, and compliance issues. He has 20 years of experience developing and deploying analytical solutions for some of the world’s largest corporations, retailers, and government agencies. Speights was formerly first vice president of Mortgage Credit Risk Modeling at Washington Mutual and chief statistician at HNC Software. He holds a Ph.D. in Biostatistics from the University of California, Los Angeles, and has several patents.

Daniel M. Downs, Ph.D., is the Senior Statistical Criminologist at Appriss and has spent the last 5 years focusing on predictive modeling. He is an author, presenter, and researcher, and has a vast background in loss prevention and criminology. Downs was a research coordinator for the Loss Prevention Research Council, where he engaged in fact-based research to develop loss control solutions to positively affect the retail industry. He received his Ph.D. in Criminology from the University of Illinois and his M.A. in Experimental Psychology from California State University, San Bernardino.

Adi Raz, MBA, is the Senior Director of Data Sciences and Modeling at Appriss and has over 15 years of experience developing analytics solutions and modeling for the retail and financial services industries. Raz has spent many years developing predictive and analytical solutions for over 30 national retailers. She manages a data sciences and modeling team and is also responsible for analytical research and development. She received her B.S. in Economics and Statistics from James Madison University and her MBA from Pepperdine University, and is currently a Business Administration doctoral candidate.

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