For undergraduate and graduate courses in Business Forecasting.

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• 1. Introduction to Forecasting.
• 2. Exploring Data Patterns and Choosing a Forecasting Technique.
• 3. Moving Averages and Smoothing Methods.
• 4. Time Series and Their Components.
• 5. Simple Linear Regression.
• 6. Multiple Regression Analysis.
• 7. Regression with Time Series Data.
• 8. The Box-Jenkins (ARIMA) Methodology.
• 9. Judgmental Forecasting and Forecast Adjustments.
• 10. Managing the Forecasting Process.
• Appendix A: Derivations.
• Appendix B: Data for Case Study 7.1.
• Appendix C: Tables.
• Appendix D: Data Sets and Databases.
• Index.