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The following forecast errors (difference between actual and forecast values) was calculated using a linear trend with seasonality model for a time series of quarterly
The following forecast errors (difference between actual and forecast values) was calculated using a linear trend with seasonality model for a time series of quarterly toy sales: The Mean Square Forecast Error (MSFE) for the forecast method is :I (please give your answer to 2 decimal places). Check The following is the list of MAD and MSFE statistics for each of the four models you have estimated from time-series data: Quadratic Trend 16.96 260.33 Linear Trend with Seasonality 18.99 209.89 Quadratic Trend with Seasonality 13.99 270.11 If it is important to weight all errors equally, the most appropriate model is Select one: 0 linear trend. 0 quadratic trend. 0 quadratic trend with seasonality. 0 linear trend with seasonality. ' Check
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