A toy company buys large quantities of plastic pellets for use in the manufacturing of its products. The production manager wants to develop a forecasting system for plastic pellet prices and is considering four different approaches and 6 different models. He plans to use historical data to test the different models for accuracy. The price per pound of plastic pellets (actual) has varied as shown Month Price/Pound 1 $0.39 2 0.41 3 0.45 4 0.44 5 0.40 6 0.41 7 0.38 8 0.36 9 0.35 10 0.38 11 0.39 12 0.43 13 0.37 14 0.38 15 0.36 16 0.39 SIMPLE LINEAR REGRESSION: Use all of the data, months 1-16, to calculate the regression equation for this data. Use the months (1-16) as the independent variable (x) and price as the dependent variable (y). Once you have the equation, forecast months 7-16 (enter 7, 8, etc. as the x value in the equation). Calculate the MAD for this forecasting model. Comment on the goodness of fit (R2) and significance of the model (F significance) to determine if this forecast model should be included in the consideration of the different approaches. (If the model is not significant, it cannot be considered, however, you must still make the forecasts and calculate the MAD). answer should be displayed in a table like below SMA AP=3 SMA AP=4 WMA ETC Month Actual Forecast Absolute Deviation Forecast Absolute Deviation Forecast Absolute Deviation 7 0.38 8 0.36
The post Calculate the MAD for this forecasting model. appeared first on Dissertation Help Service.