The eighth edition of Business Forecasting presents basic statistical techniques that are useful for preparing individual business forecasts and long-range plans. Written in a simple, straightforward style and making extensive use of practical business examples, the book includes fifty-three cases that provide readers with the necessary link between theoretical concepts and their real-world applications. Readers should have a basic knowledge of statistics and be familiar with computer applications such as word processing and spreadsheets. The book first presents background material such as the nature of forecasting and a quick review of basic statistical concepts; proceeds with the exploration of data patterns and choosing a forecasting technique; covers averaging the smoothing techniques and time series decomposition; emphasizes causal forecasting techniques such as correlation, regression, and multiple regression analysis; and concludes with judgmental forecasting and forecast adjustments. Useful as a reference for professionals with titles such as: forecasting manager, marketing manager, production manager, and analyst.



Book Info

(Pearson Education) A textbook aiming to present the statistical techniques useful for preparing individual business forecasts and long-range plans. Emphasis is placed on the application of decision-making techniques by management. Includes 46 case studies and real-world applications for all topics covered.

The publisher, Prentice Hall Business Publishing

This top selling text presents, in a straightforward, application-driven manner, the basic statistical techniques that are useful for preparing individual business forecasts and long-range plans. The emphasis is on the application of techniques by management for decision-making.

From the Back Cover

Managerial decision-making in approach, this book explores the basic statistical techniques that are useful for preparing individual business forecasts and long-range plans. Incorporates instructions on using Excel spreadsheets and the statistical package MINITAB to forecast, along with their appropriate output. Organizing Data and a Review of Statistical Concepts. Exploring Data Patterns and Choosing a Forecasting Technique. Moving Averages and Smoothing Methods. Time Series Analysis. Regression Analysis. Multiple Regression. Regression with Time Series Data. The Box-Jenkins (ARIMA) Methodology. Judgmental Forecasting and Other Forecasting Methods. Managing the Forecasting Process. For business managers interested in business forecasting techniques.