For undergraduate and graduate courses in Business Forecasting.
Written in a simple, straightforward style, Business Forecasting, 9th Edition presents basic statistical techniques using practical business examples to teach readers how to predict long-term forecasts.
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Höhe: 10 mm
Breite: 10 mm
Dicke: 10 mm
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ISBN-13
978-0-13-230120-6 (9780132301206)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
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 internet.
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 spreadsheets.
The authors have tried several different approaches to help faculty and students use the computer for forecasting. This edition features the following:
Minitab instructions presented at the end of most chapters.
Excel instructions presented at the end of most chapters.
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.
Examples of different computer outputs are placed throughout the text.
Brief Contents
Introduction to Forecasting
A Review of Basic Statistical Concepts
Exploring Data Patterns and Choosing a Forecasting Technique
Moving Averages and Smoothing Methods
Time Series and Their Components
Simple Linear Regression
Multiple Regression Analysis
Regression with Time Series Data
The Box-Jenkins (ARIMA) Methodology
Judgmental Forecasting and Forecast Adjustments
Managing the Forecasting Process
Appendix A: Derivations Appendix B: Data for Case Study 7.1 Appendix C: Tables Appendix D: Data Sets and Databases
