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Prism 5 does not use precisely the same algorithm as did Prism 4, so curve fitting results can be different in rare cases:
| • | If your fit is labeled "Ambiguous" by Prism 5, you know that you have a problem. See these suggestions for dealing with ambiguous fits. Prism 4 presented a full set of results in this case, but the results are not useful when the fit is ambiguous. |
| • | If you chose no weighting, check the sum-of-squares from the two programs. The goal of regression is to minimize that sum of squares, so see which version of Prism found a fit with the smaller sum-of-squares. Prism 5 has a few improvements in the fitting algorithm, so occasionally it can find a better fit than did Prism 4. The differences, if any, are usually trivial. |
| • | If you chose to weight by the Y values (or the Y values squared), Prism 5 handles weighting differently than did Prism 4. Prism 5 weights by the Y value of the curve, while Prism 4 (and earlier releases) weighted by the Y value of the data. The method used by Prism 5 is better, so the results of Prism 5 are more correct. Since the weighting is computed differently, you can't directly compare the weighted sum-of-square values reported by the two versions of Prism. |
| • | When you compare two models, Prism 5 does an extra step. If one of the models is ambiguous, then Prism chooses the other model, without doing the F test or AIC comparison. |
| • | Prism 5 offers more rules for defining initial parameter values. If your equation uses one of these new rules, Prism 4 might not be able to find a reasonable fit until you tweak those initial values. |
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