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Core
CLT, Sampling, and Confidence Intervals
The central limit theorem says the mean of a sample is approximately normal regardless of the underlying distribution, which is why so much inference uses the normal curve. Standard error measures how much a sample mean wobbles and shrinks with sample size, unlike standard deviation. Applied-AI interviews probe this because it sets how wide a confidence interval is and therefore how long an A/B test must run.
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RELATED CONCEPTS
PRACTICE THIS IN REAL QUESTIONS
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