Even A/B tests with well-conceived test concepts can lead to non-significant results and erroneous interpretations. And this can happen in every phase of testing if incorrect statistical approaches are used. This post will illustrate the 10 most important statistical traps to be aware of.
I. Statistics traps before testing Statistics trap #1: Too many variants Let’s test as many variants as possible; one of them will surely work. In most cases, testing too many variants at once is n...
Even A/B tests with well-conceived test concepts can lead to non-significant results and erroneous interpretations. And this can happen in every phase of testing if incorrect statistical approaches are used. This post will illustrate the 10 most important statistical traps to be aware of.
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10 Statistics Mistakes and Traps in A/B Testing: The Guide for Optimizers
I. Statistics traps before testing Statistics trap #1: Too many variants Let’s test as many variants as possible; one of them will surely work. In most cases, testing too many variants at once is n...
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