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I have a statistics doubt. Consider I have the following values.

Base Model      Model 1     Model 2 5               7           4 10              12          8 15              17          12 20              23          21 25              30          27 30              31          31 35              34          37 40              43          43 45              45          44 50              51          50 

I want a better way to represent Model1 and Model2 by comparing against the Base Model. I used an error metric:

$\frac{|\text{My_Model} - \text{Base_Model}|}{\text{Base_Model}} \times 100$

What other methods can I use to represent these. I want to plot these as a graph and see how good Model 1 and Model 2 are w.r.t Base Model. Can I use any form of distributions?

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    What is your research question?2012-08-24

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In the chi square goodness of fit test the measure is ∑(observed-expected)$^2/expected. The change to your formula would be to square the numerator and not express it as a percentage.