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I want to compare (statistically) different models which predict the values y at several x-values. Therefore I want to calculate the 'total error' between the exact (measured) y-values and the calculated y-values using different models. My problem is that I'm not sure which method to use to calculate the 'total error' for each model. Should I use the sum of squared errors, the sum of the absolute errors or some other technique?

Thanks

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# Which error should I calculate?

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