Ideally, the confidence interval should contain 0. The standard deviation is computed as well as a confidence interval. If replicates are available, a first step computes the mean of the replicates. The bias is estimated as the mean of the differences between the two methods. If the data are randomly scattered around the identity line with some observations that are far from it, the new method is not performing well. If the data are crossing the identify line, there is a bias that depends on where you are on the scale of variation.
If the data are under the line, the new method underestimates the value of interest, at least compared to the comparative or reference method. If the data are above the identify line, the new method overestimates the value of interest. If the data are on both sides of the identity line (bisector) and close to it, the two methods give close and consistent results. Scatter plots for comparing methodsįirst, you can draw a s catter plot to compare the reference or comparative method against the method being tested. The paired t-test allows to test the null hypothesis H0 that the mean of the differences between the results of the two methods is not different from 0, against an alternative hypothesis Ha that it is. Paired t-test for method comparisonĪmong the comparison methods, a paired t-test can be computed.
#XLSTAT HISTOGRAM FOR NON SCALE DATA SERIES#
XLSTAT provides a series of tools to evaluate the performance of a method compared to another. In addition If a new measurement method is preferred for economic reasons, but do not performed as good as the reference method, you might take into account the bias while reporting the results. It may be due to a bias that depends on the position on the scale variation. If there is a difference, you should investigate the reasons. When developing a new method you might want to be sure that the results are similar to a reference or a comparable method.
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