This book emphasizes the rationale, application, and interpretation of the most commonly used forecasting techniques in business.
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A. Reza Hoshmand is associate dean of graduate studies and chair of the Business and Management Division at Daniel Webster College. He holds a Ph.D. in resource economics from the University of Maryland and has published nearly a dozen books and manuals, including Design of Experiments for Agriculture and the Natural Sciences, 2nd Edition (Chapman and Hall\CRC Press, 2006), Business and Economic Forecasting for the Information Age: A Practical Approach (Quorum, 2002) and, Statistical Methods for Environmental and Agricultural Sciences, Second Edition (CRC Press, 1997.) He has also written more than two dozen journal articles, technical reports and other papers.
Recently named a Fulbright Scholar to research foreign direct investment in China, Professor Hoshmand has garnered numerous other honors and awards including being nominated for the "Excellence in Teaching Award" by the University of Hawaii Board of Regents and being included in Who's Who in the West, 26th edition. Prior to coming to Daniel Webster in 2001, Professor Hoshmand was a Professor of Economics and Finance at Lesley University's School of Management. He has been a faculty member at the University of Hawaii, and with the California State University at Pomona. At Cal Poly Pomona, he was the interim director, International Center, and associate dean, College of Agriculture. He also held numerous other academic appointments during his career, including economics lecturer at Harvard and Tufts Universities. In 1991 Professor Hoshmand, was a visiting lecturer, economics, at the University of Hong Kong.
Inhaltsangabe
1. Forecasting for Management Decisions: An Introduction 2. Data Patterns and Choice of Forecasting Techniques 3. The Macroeconomy and Business Forecasts 4. Data Collection and Analysis in Forecasting 5. Forecasting with Smoothing Techniques 6. Adaptive Filtering as a Forecasting Technique 7. Forecasting with Simple Regression 8. Forecasting with Multiple Regression 9. Advanced Regression Methodologies in Forecasting 10. The Box-Jenkins Method of Forecasting 11. Communicating Forecasts To Management. Appendix: Statistical Tables
1. Forecasting for Management Decisions: An Introduction 2. Data Patterns and Choice of Forecasting Techniques 3. The Macroeconomy and Business Forecasts 4. Data Collection and Analysis in Forecasting 5. Forecasting with Smoothing Techniques 6. Adaptive Filtering as a Forecasting Technique 7. Forecasting with Simple Regression 8. Forecasting with Multiple Regression 9. Advanced Regression Methodologies in Forecasting 10. The Box-Jenkins Method of Forecasting 11. Communicating Forecasts To Management. Appendix: Statistical Tables
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