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Prentice Hall Professional Technical Reference
Business Forecasting / Edition 6

Business Forecasting / Edition 6


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Product Details

ISBN-13: 9780137607457
Publisher: Prentice Hall Professional Technical Reference
Publication date: 08/14/1997
Edition description: Older Edition
Pages: 581
Product dimensions: 7.81(w) x 9.59(h) x 1.08(d)

About the Author

John E. Hanke

Eastern Washington University, Emeritus

Dean W. Wichern

Texas A&M University

In the first eight editions, the computer was recognized as a powerful tool in forecasting.

The computer is even more important now with the availability of powerful

forecasting software and easy access to data via networking capabilities and the


A nationwide research study of all AACSB member institutions conducted by

the authors to determine what faculty do about using computers for teaching forecasting

showed that (1) most forecasting faculty (94.2%) attempt to provide

students with hands-on experience in using the computer, and (2) several statistical

packages and specific personal computer forecasting packages were mentioned in

the survey. The packages mentioned most frequently were Minitab, SAS, and


The authors have tried several different approaches to help faculty and students

use the computer for forecasting.This edition features the following:

1. Minitab instructions presented at the end of most chapters.

2. Excel instructions presented at the end of most chapters.

3. Three data collections available on the Internet (Minitab, Excel, other programs).

Each collection contains data from the text examples and problems. Each collection

also contains several new data series.To access the data sets on the Internet go

to the Prentice Hall Web site at

4. Examples of different computer outputs are placed throughout the text.

Table of Contents

1. Introduction to Forecasting.
2. A Review of Basic Statistical Concepts.
3. Data Sources.
4. Exploring Data Patterns and Choosing a Forecasting Technique.
5. Moving Averages and Smoothing Methods.
6. Regression Analysis.
7. Multiple Regression.
8. Time Series Analysis.
9. Regression of Time Series Data.
10. The Box-Jenkins (ARIMA) Methodology.
11. Judgmental Elements in Forecasting.
Appendix A. Derivations.
Appendix B. Data for Case Study 7.1.
Appendix C. Tables.
Appendix D. Data Sets and Database.

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