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Effect size

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Also known as an effect.

The observed difference in performance between variants.

Or more simply stated, the conversion rate difference between versions.

In testing, your goal is to ensure you've accurately detected a meaningful effect, or conversion difference.

To do so, you need an adequate sample size so you test has enough power to accurately pick up a real effect so you're not making a type I or type II error.

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