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I need to do a statistical test for one of my study but I’m not sure which test is appropriate.

This is my experiment:

I measured performance of 30 tools (F1 scores) on classifying a pair of documents as similar or not. Then, I applied an enhancement process to every tool and measured the tools performance again (they are the same set of tools before and after the process). I found that the enhancement can increase the F1 scores of every tool. However, I would like to test if the performance "improvement" has statistical significance. The 30 tools work deterministically.

I read from a few places that it would be a either a parametric paired t-test or a non-parametric Wilcoxon test depending on the normality of my data. So I tried using Shapiro–Wilk test on both the before and after data, they're not normally distributed (p-value = 5.177e-05 and 0.008338).

So should I go for Wilcoxon test? If not, could you please recommend a test that I should use?

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Paired :-)test because you're measuring the same group of documents. Is this numerical or categorical data?


I'm sorry, I believe not paired because the two types of analysis you're comparing are not related. A simple t test with pooled variance should work, unless you believe the two sets of data have a different variance.

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  • $\begingroup$ Your two different answers have been edited together. Please edit your answer to choose a single position, but offer better support for whichever it is you now think is correct. $\endgroup$ – Glen_b -Reinstate Monica May 30 '17 at 23:13

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