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Advanced power for experimentation programs: simulation-based power, cluster and geo designs, multiplicity, sequential and optional stopping, variance reduction, and aligning analysis models with power assumptions. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Planning and interpreting power for product experiments: effect sizes, variance, two-proportion and mean tests, one- vs two-sided tests, and minimum detectable effects. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Foundations of statistical power: Type I/II errors, significance level, sample size intuition, and why underpowered experiments miss real effects. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
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