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← Study plan·Math & Stats

Day 7 of 133

Stats consolidation + DSA Sliding Window kickoff

Quick recap of week 1 stats; rehearse Bayes, CLT, p-values, A/B; start Sliding Window.

DSA · NeetCode Sliding Window

  • Longest Repeating Character ReplacementDSA · Sliding Window

    Interview questions to prep

    1. Is this a fixed-size or variable-size window? Why does that fit this problem?
    2. What's the invariant inside the window, and how do you maintain it on shrink/expand?
    3. Why is the overall pass O(n) even though the inner loop looks like it could be O(n²)?
  • Permutation IN StringDSA · Sliding Window

    Interview questions to prep

    1. Is this a fixed-size or variable-size window? Why does that fit this problem?
    2. What's the invariant inside the window, and how do you maintain it on shrink/expand?
    3. Why is the overall pass O(n) even though the inner loop looks like it could be O(n²)?

Math · Probability fundamentals

  • Probability axioms, sample spaces, joint / marginal / conditionalStatisticsInteractive

    Interview questions to prep

    1. What's the difference between joint, marginal and conditional probability — give a worked example?
    2. When is independence the same as conditional independence? Why does the distinction matter for Naive Bayes?
    3. Explain the law of total probability with a churn-prediction example.
  • Bayes' theorem: priors, likelihood, posteriorStatisticsInteractive

    Interview questions to prep

    1. Walk through Bayes on a screening test (1% prevalence, 95% sensitivity, 90% specificity) — why is positive predictive value still low?
    2. How would you use Bayes to update belief during an A/B test as data arrives?
    3. When does using a strong prior hurt vs help in production ML?
  • Conditional probability traps & base-rate fallacyStatisticsRead

    Interview questions to prep

    1. Two children: at least one is a girl. What's the probability the other is also a girl? Defend your answer.
    2. Why is P(disease|positive) ≠ sensitivity in general?
    3. Explain the base-rate fallacy with a hiring or fraud example.

Math · A/B testing in production

  • Experiment design: power, MDE, randomization, SRMStatisticsEvan Miller

    Interview questions to prep

    1. How do you choose sample size for an A/B test? What's MDE?
    2. What is sample-ratio mismatch (SRM) and why is it a red flag?
    3. Walk through how to design an experiment to detect a 1% lift in conversion.
  • Sequential / peeking problems & remediesStatisticsEvan Miller

    Interview questions to prep

    1. Why does 'checking the test daily and stopping when significant' inflate Type I error?
    2. What are sequential testing methods (e.g., always-valid p-values) and when would you use them?
  • Variance reduction: stratification & CUPEDStatisticsMicrosoft

    Interview questions to prep

    1. Explain CUPED in plain English. Why does it shrink confidence intervals?
    2. What's the difference between stratification and CUPED for variance reduction?

References & further reading