• 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.

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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.

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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.

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