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Explain Central Limit Theorem's Importance in A/B Testing

Last updated: Mar 29, 2026

Quick Overview

This question evaluates understanding of the Central Limit Theorem, sampling distributions, confidence-interval construction, and their application to A/B testing within the Statistics & Math domain.

Statistics Knowledge Check: CLT, A/B Testing, and Confidence Interval

Context

You are in a data science interview. Answer the following about the Central Limit Theorem (CLT), its relevance to A/B testing, and construct a confidence interval for a mean with known population standard deviation.

Questions

State the Central Limit Theorem (CLT) and explain why it matters for A/B testing.
Given a sample mean of 3, a known population standard deviation of 1, and n = 400, construct a 95% confidence interval for the population mean.
On a whiteboard, sketch the sampling distribution of the sample mean for part (2) and mark the 95% confidence bounds.

Solution

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