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What is an A/A test, and why is it needed?
In an A/B test, 5 out of 100 metrics show a statistically significant positive result, while the rest are neutral. Should we roll out the change?
Explain the difference between covariance and correlation. When can Pearson correlation be zero despite a dependency?
What is a p-value? Does p-value = 0.03 mean there's a 3% chance the null hypothesis is true?
Explain the Central Limit Theorem and why it's important for A/B testing.
How to calculate sample size for an A/B test? What parameters are needed and how do they affect n?
What is bootstrap? How to construct confidence intervals with it? When is bootstrap better than analytical formulas?
Bayesian vs frequentist A/B testing: what's the difference and when to choose Bayesian?
A/B test: control conversion 10%, want to detect 0.5% absolute lift. Day 3 p-value = 0.03. Should you stop?
Explain Simpson's paradox with an ML/analytics example where ignoring a confounder leads to wrong conclusions.
What is a 95% confidence interval? Is it correct to say 'there's a 95% probability the true parameter is in this interval'?
How to assess statistical significance for ratio metrics (e.g., revenue per user) in A/B tests? Why can t-test be incorrect?
Explain the Monty Hall problem using Bayesian updating. Generalize to n doors.
Explain CUPED. Derive the optimal θ and show the variance reduction.
Derive the posterior for Bayesian updating with normal likelihood and normal prior. How is this related to ridge regression?
How to correctly run A/B test with multiple metrics (5+ KPIs)? Explain multiple comparisons problem and correction methods.
Explain the delta method for variance estimation of nonlinear functions of random variables. Give an example for ratio metrics in A/B tests.
Можешь сказать, в каком интервале будут находиться значения логарифмированной вероятности?
Можешь сказать, как мы можем рассчитать вероятность того, что тысячу раз подбросили и тысячу раз у нас выпал орел?
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