Answer core probability and inference questions

Q: Answer core probability and inference questions

This question evaluates understanding of statistical inference and probability fundamentals, covering the Central Limit Theorem, p-values, Type I and Type II errors with power and significance, sample size considerations, and the distinction between correlation and causation.

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You are interviewing for a Data Scientist role. Explain/derive the following statistics fundamentals.

State the Central Limit Theorem (CLT) . What conditions are needed, and what does it imply about sample means?
What is a p-value ? What is a common misinterpretation?
Define Type I and Type II errors and relate them to significance level (α) and power (1−β) .
How do you think about sample size requirements for hypothesis tests (what inputs matter)?
Explain the difference between correlation and causation . Give at least two reasons correlation may not imply causation in observational data.

Answer core probability and inference questions

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Answer core probability and inference questions

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