multiple choice

What the Central Limit Theorem lets you do

Statistics & Inference · Foundations · easy · Company-context scenario · 6 min

Why does the Central Limit Theorem matter for A/B testing, where the underlying metric (e.g. revenue per user) is highly skewed?

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Picks the option the reasoning in the prompt supports

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Company-context scenario built from real product constraints. It is not represented as a verbatim interview question.

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A. It says the distribution of the SAMPLE MEAN approaches normal as n grows, even when the underlying data is skewed — so we can use normal-based tests on the meanB. It removes the need for a large sample sizeC. It says the raw data becomes normally distributed if you collect enough of itD. It guarantees the two groups have equal variance

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What the Central Limit Theorem lets you do

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