PRINCIPLES OF BUSINESS FORECASTING KEITH ORD PDF

Forecasting, the Why and How. Basic Tools for Forecasting. Forecasting Trends: Exponential Smoothing. Seasonal Series: Forecasting and Decomposition. State-Space Models for Time Series.

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Whether used by students or current practitioners, this book provides an introduction to both standard and advanced forecasting methods and their underlying models, and also includes general principles to guide and simplify forecasting practice.

Forecasting techniques are demonstrated using a variety of software platforms and the companion website provides easy-to-use Excel macros to support the basic methods. After the introductory chapters, the focus shifts to using extrapolative methods exponential smoothing and ARIMA and then to statistical model-building using multiple regression. In later chapters, the authors cover more novel techniques such as data mining and judgmental methods, and also examine organizational issues of implementation and the development of a forecasting support system within an organization.

He completed his graduate work at the University of London and held faculty positions at the Universities of Bristol and Warwick before moving to The Pennsylvania State University in and then to Georgetown University in His research interests include time series and forecasting, spatial modeling and the statistical modeling of business processes. He has a mathematics degree from Oxford and a Ph. He was president of the International Institute of Forecasters between and His research interests are concerned with the comparative evaluation of different forecasting methods, the implementation of improved forecasting procedures in organizations and the design of forecasting systems.

In he wrote one of the earliest business forecasting textbooks. Though long out-of-print, many of its core ideas have survived the test of time. Review: 1. Forecasting, the Why and How. Basic Tools for Forecasting. Forecasting Trends: Exponential Smoothing. Seasonal Series: Forecasting and Decomposition.

State-Space Models for Time Series. Simple Linear Regression for Forecasting. Multiple Regression for Time Series. Model Building. Advanced Methods of Forecasting. Judgment-Based Forecasts.

Putting Forecasting Methods to Work. Forecasting in Practice. Appendix A: Basic Statistical Concepts online only. Appendix B: Glossary online only. Appendix C: Forecasting Software online only.

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