Quantitative Forecasting Methods
Quantitative Forecasting Methods
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Quantitative Forecasting Methods by Nicholas Farnum
This text is designed for practitioners and students of applied statistical forecasting. It is suitable for both the undergraduate or graduate business student. The text presents structured, detailed discussions of the concepts, and step-by-step procedures for using current forecasting methods. It is assumed that the reader has a knowledge of basic algebra and statistics. The text organizes the study of forecasting by using the classical trend, seasonal, and cycle approach to differentiate between the methods presented. Each chapter is organized with an overview, illustrations of concepts, decision factors in using the particular technique, model fitting and forecasting, and diagnostic testing. Several forecasting methods are covered such as exponential smoothing, leading indicator, business cycle, adaptive forecasting, time series application of regression analysis, and relevant government time series techniques.
Farnum, Nicholas R.: - Nicholas Farnum received his B.S. and Ph.D. in Mathematics from University of California at Irvine. He is currently a professor in the Information Systems and Decision Sciences Department at California State University, Fullerton. Professor Farnum has published several papers in applied and theoretical statistics and has also written texts in Quality Control and Forecasting. He is a member of the American Statistical Association and the Mathematical Association of America. In his spare time Professor Farnum enjoys cooking, playing music, and traveling.
| SKU | Nicht verfügbar |
| ISBN 13 | 9780534916862 |
| ISBN 10 | 0534916864 |
| Titel | Quantitative Forecasting Methods |
| Autor | Nicholas Farnum |
| Buchzustand | Nicht verfügbar |
| Verlag | Pws Pub Co |
| Erscheinungsjahr | 1997-08-15 |
| Seitenanzahl | 656 |
| Hinweis auf dem Einband | Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden. |
| Hinweis | Nicht verfügbar |