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# Forecasting and Seasonality

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I need to forecast out 12 months using 3 different techniques, and then decide which one is best based on MAD (mean absolute deviation).

Using some historical data for the past 40 periods (see attachment) I need to make a forecast for the next 12 periods (periods 41 thru 52) using 3 of the simple forecasting techniques we have covered so far in our 2nd year class. These include: 1)Simple Moving Average 2)Weighted Moving Average 3)Exponential Smoothing 4)Linear Regression 5)Seasonal Forecasting via Regression, if we determine it is subject to seasonality (i.e., linear trends with multiplicative seasonality or nonlinear trends with multiplicative seasonality, and linear trends with additive seasonality or nonlinear trends with additive seasonality)

Using Excel or the Excel add-in Crystal Ball (we may NOT use Minitab, SAS, JMP, or any other packages), we need to investigate AT LEAST 3 different ways to forecast this data, and present the MAD (mean absolute deviation) and parameter values of each technique we tried. And then pick whatever is the "best forecast" based on the MAD...

I do not know how to do this. I think seasonality may be one technique we need to look at, because the prof mentioned it would be one to look out for...but how do we know if demand is affected seasonally???