#ask-questions

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orange-train-515

12/13/2021, 9:32 AMHi. My understanding is that the statistical significance for non-binomial metrics is calculated somewhat different and uses different statistical approaches, is that correct?

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fresh-football-47124

12/13/2021, 9:33 AM

Hi Eugene, yes, you can read about the stats we use here: https://www.growthbook.io/docs/GrowthBookStatsEngine.pdf

does that answer your question?

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future-teacher-7046

12/13/2021, 1:00 PM

Both binomial and non-binomial use the same basic statistical approach, just with different Bayesian priors. Binomial uses beta-binomial priors and everything else uses gaussian priors.

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breezy-crowd-53224

12/13/2021, 1:30 PMsorry to ‘highjack’ this question , but should we assume any type of distribution of the data for continuous data? should not matter if I’m correct?

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future-teacher-7046

12/13/2021, 2:10 PM

With enough samples, the central limit theorem should apply. If your data is extremely skewed, we recommend adding a cap to the value (e.g. normal orders are $10, but you get a $1000 bulk order occasionally)

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breezy-crowd-53224

12/13/2021, 2:42 PMk that’s helpful. Using frequentist approach I do notice quite a difference between using Mann Whitney U versus regular TTest. So central limit theorem apparently is not the complete story or doesn’t apply somehow 😉
Was wondering how this is handled in bayesian testing

I presume capping should be done in our data / SQL right?

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future-teacher-7046

12/13/2021, 2:51 PM

You can set a capped value in the metric behavior settings. We're looking into adding more prior options for extremely skewed distributions

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breezy-crowd-53224

12/13/2021, 3:33 PMoh that’s awesome 🙂

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