Master the full hypothesis testing framework used in data science interviews. Covers p-values, confidence intervals, Type I/II errors, power analysis, choosing the right test, and common gotchas interviewers love to probe.
Framework: 1) State hypotheses, 2) Choose significance level α, 3) Select test statistic, 4) Compute p-value, 5) Reject/fail to reject H₀, 6) Interpret practically. Understand power, sample size tradeoffs, and when normality assumptions break.
Ready to practice?
Write your structured answer, then compare to a strong model answer.