# How to quantify statistical insignificance?

I'm relatively new to statistics, and understand that my question may be completely misworded. I am testing my own algorithm versus another. While the outputs are not identical, I want to show that the differences are "statistically insignificant." How can I quantify this, to make my point?

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That'll depend on what kinds of data you're dealing with, and how big your samples are. Can you edit your post to include a more detailed answer? –  naught101 May 22 '12 at 2:32
The equivalence test is powwered to reject nonequivalence. It forces you to pick the sample size large enough to have power. Without reversing the null and alternative hypothesis in small samples you would have very little change of rejecting the null hypothesis of no difference. But not rejecting is not the same as accepting because of the lack of power, That is why Blackwelder makes non-equavalence the null hypothesis and showing equivalence requires rejecting the null. –  Michael Chernick May 22 '12 at 3:23
Note that the null hypothesis is that the difference in means is greater that a specified delta (the window of equivalence). –  Michael Chernick May 22 '12 at 3:23