Quantitative Forecasting Methods (The Duxbury series in statistics and decision sciences)

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.