Predictive Analytics For Business Using R - Softcover

Barton, Russell R

Softcover

ISBN 10: 9819820340 ISBN 13: 9789819820344

Publisher: WSPC, 2024

Synopsis

Predictive Analytics for Business using R by Russell R Barton equips business professionals and students with the tools to forecast trends, classify outcomes, and analyze time-dependent data using R programming. Focused on real-world business applications, the book covers essential topics such as regression analysis, classification models, time series forecasting, and simulation. It emphasizes how to assess uncertainty and interpret model results with confidence. Designed for case-based learning, each chapter is paired with real data and accompanying R code — making it ideal for hands-on practice in academic or professional settings. Whether you're analyzing customer behavior, forecasting sales, or modeling system performance, this book offers the analytical foundation to make smarter, data-driven decisions.

About this title

About the Author

Russell Barton is Distinguished Professor of Supply Chain and Information Systems in the Smeal College of Business and a Certified Analytics Professional. He received his PhD in operations research from Cornell University. He began his career as an analytics consultant at RCA, followed by similar roles at Econ, Inc., The Mentoris Company, and Mathtech, before returning to RCA for eight years. Projects included predicting the impact of telecommuting on urban structure, modeling exoffender post-release behavior, analyzing workers' compensation claims for hundreds of thousands of records, constructing risk models for self-insurance options, simulating semiconductor manufacturing operations, predicting satellite communications reliability, measuring videodisc quality, characterizing image errors in video monitors, and visual representations of experiment results. His academic career began at Cornell University as a Visiting Associate Professor in the School of Operations Research and Industrial Engineering, and Laboratory Director for the Cornell Computational Optimization Project. Following Cornell, he was Professor of Industrial Engineering at Penn State. From 1998–1999 he was a Visiting Professor at Ècole Centrale Paris in the Production and Logistics Research Laboratory. He moved to Penn State's Smeal College of Business in 2002, and served as Associate Dean for Research and MS/PhD Programs, Co-Director of the Master's of Manufacturing Management degree program, and as Senior Associate Dean for Research and Faculty. served as Program Director for Manufacturing Enterprise Systems and Service Enterprise Systems at the US National Science Foundation from 2010–2012, and as an analytics consultant to firms including Fluke, Ford, GE, GM, Kodak, Lockheed-Martin, Textron, and Xerox.

Edition details

• Publisher: WSPC
• Publication date: 2024
• Language: English
• ISBN 10: 9819820340
• ISBN 13: 9789819820344
• Binding: Paperback
• Number of pages: 464