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Forecast Errors
Differences among actual results and predictions may arise from many reasons. They may arise from random influences, usual sampling errors, option of the wrong forecasting system or alpha value or only that the future conditions turn out to be radically different from the past. Whatever the cause or causes management wish to know the extent of the forecast errors and different methods exist to calculate these errors.
A commonly utilized technique, suitable to time series, is to calculate the mean squared error of the deviations between actual and forecast values then choose the forecasting system and/or parameters which gives the lowest value of mean squared errors that is akin to the 'least squares' method of establishing a regression line.
Once we get out of the review, we are not going to be doing a lot with Taylor series, but they are a fine method to get us back into the swing of dealing with power series. Through
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25 algebraic equations that equal 36
HOW DO WE CAN SOLVE SIMPLIFY?
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