| Guolin Lai DSC8240 Course Web |
Business
Modeling for Decision Support |
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Personal Statement Chapter 1 Summary Chapter 2 Report Breakeven Analysis Price & Demand Relationship Quantity Discounts Decision Hedging Investment Risk Time Value of Money Enterprise DSS Time Series Forecasting DSS Development Project Simulation Model Examples Government Contract Bidding GFAuto Model Customer Loyalty Game of Craps Monte Carlo Simulation Optimization Modeling Term Project Business Intelligence Research |
Time Series Forecasting
Background
Forecast the stereo sales based on the Excel file from the Chapter 16 using CB Predictor and StatPro.
Objective
To evaluate the following different forecasting methhods:
Decision Variables
Previous seasonal sales (12 months in a year as a cycle).
The data included 4 years of monthly data from Jan. 1995 to Dec. 1998, downloaded from course website..
Forecast Spreadsheets
Evaluation Based upon the practice with StatPro and CB Predictor, we found out that, even though Microsoft Excel itself has in itself the data analysis tools such as Moving Averages and Exponential Smoothing, StatPro forecasting tool is significantly powerful, visual, and efficient, which offers a series of ways of forecasting. While for CB Predictor, all potentially available forecasting mechanisms (Single Moving Average, Double Moving Average, Single Exponential Smoothing, Double Exponential Smoothing, Seasonal Additive, Holt-Winters' Additive, Seasonal Multiplicative, and Holt-Winters' Multiplicative) are combined into a user-friendly procedure, and it will finally suggest the best forecasting method. Winters' Model from CB Predictor provides the best forecasting. Click here to view the Microsoft Excel file of furniture sales by using time series techniques. |
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