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Null Hypothesis

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The opposite of the result you’re trying to prove.

In A/B testing, the goal is to show one variant outperforms the other. But, a null hypothesis assumes there’s no difference between variants A and B; both perform equally effectively.

When you run an A/B test and discover, for example, variant B converts 5% better than variant A, your null hypothesis is proven incorrect.

You find there is indeed a difference between versions A and B.

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