Statistics & Math Interview Questions

Showing 1–30 of 124 results

• AdobeEasy·Data Scientist
  Understand P-Value's Role in Product Decision-Making

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Understand P-Value's Role in Product Decision-Making states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite
• AmazonMedium·Data Scientist
  Calculate A/B sample size, CI, decision rules

  This question evaluates skills in experimental design and statistical inference, including sample size calculation, hypothesis testing, confidence interval interpretation, multiple comparison control, variance reduction techniques, and operational considerations for A/B testing.

  Statistics & MathOnsite
• AmazonMedium·Applied Scientist
  Compute and Explain Mean and Variance

  This question tests your understanding of statistical estimators for mean and variance, the derivation of Bessel's correction, catastrophic cancellation in naive computations, and numerically stable single-pass algorithms like Welford's.

  Statistics & MathOnsiteStatisticsNumerical AnalysisAlgorithms
• AmazonHard·Data Scientist
  Estimate Treatment Effects Using PSM, DiD, and DML Methods

  Estimate Treatment Effects Using PSM, DiD, and DML Methods evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite
• AmazonMedium·Data Scientist
  Identify P-Value Limitations and Complementary Approaches

  Identify P-Value Limitations and Complementary Approaches evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite
• AmazonMedium·Applied Scientist
  Mean and Variance Through Maximum Likelihood

  Derive the maximum likelihood estimators (MLE) for the mean and variance of a univariate Gaussian distribution, and analyze the bias of the resulting variance estimator.

  Statistics & MathOnsitemaximum-likelihoodgaussian-distributionbias-variance
• AppleMedium·Data Scientist
  Differentiate P-value and Confidence Interval in Statistics

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Differentiate P-value and Confidence Interval in Statistics states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite
• Capital OneEasy·Data Scientist
  Compute Optimal Die Re-roll Strategy

  This question tests the ability to calculate expected values and determine optimal decision thresholds in a multi-stage probabilistic game.

  Statistics & MathOnsiteProbabilityExpected ValueDecision Theory
• Capital OneMedium·Data Scientist
  Compute credit-card portfolio profit and breakeven

  This question evaluates financial modeling, unit-economics calculation, breakeven analysis, and basic risk/expected-loss estimation relevant to a Data Scientist, testing competency in statistics & math and algebraic derivation within financial analysis.

  Statistics & MathOnsite
• Capital OneMedium·Data Scientist
  Compute expansion profits and expected value

  This question evaluates financial modeling, expected-value decision-making, probability reasoning, and sensitivity analysis skills applied to revenue, variable and fixed cost interactions and contractual fee impacts, aimed at a Data Scientist role.

  Statistics & MathOnsite
• Capital OneMedium·Data Scientist
  Determine Claim Rate for Breakeven in Insurance Portfolio

  Evaluates weather-insurance portfolio profitability from premiums, servicing, regulatory costs, and expected claims. Strong answers derive break-even claim rate, segment-selection rules, and incremental profit formulas.

  Statistics & MathOnsite
• Capital OneHard·Data Scientist
  Diagnose and fix a flight-delay modeling setup

  This question evaluates proficiency in statistical modeling for binary outcomes, including concepts such as appropriate model choice and link functions, categorical encoding, ETL-driven data quality issues, multicollinearity diagnostics (e.g.

  Statistics & MathOnsite
• Capital OneMedium·Data Scientist
  Estimate Default Rates Using Logistic Regression Model

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Estimate Default Rates Using Logistic Regression Model states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite
• Capital OneMedium·Data Scientist
  Interpret regression metrics and assumptions

  This question evaluates a candidate's mastery of multiple linear regression diagnostics and interpretation, covering standardized coefficient interpretation and significance, R²/adjusted R² and out‑of‑fold RMSE comparisons, multicollinearity detection and its effect on coefficients and SEs, heteroskedasticity diagnostics and robust remedies, and implications of intercept omission and partial standardization. Commonly asked in data scientist interviews within the Statistics & Math domain because it probes both conceptual understanding of statistical inference and practical application of model diagnostics and adjustments for reliable prediction and inference.

  Statistics & MathOnsite
• Capital OneMedium·Data Scientist
  Model network-service unit economics and breakeven

  This question evaluates a data scientist's ability to model unit economics, calculate per-customer contribution and breakeven, and conduct sensitivity and probabilistic churn analysis.

  Statistics & MathOnsite
• Capital OneMedium·Data Scientist
  Quantify and Model Flight Delays Using Statistical Tests

  Evaluates flight-delay quantification, modeling, and mitigation testing using historical operational data. Strong answers define delay metrics, model delay probability and severity, avoid leakage, and design valid experiments.

  Statistics & MathOnsite
• CitadelHard·Data Scientist
  Solve Classic Probability Questions

  This problem tests your ability to calculate the expected stopping time of a stochastic process and your proficiency with the linearity of expectation in the context of sequential probability.

  Statistics & MathOnsiteProbabilityExpectationStochastic Processes
• CitadelHard·Data Scientist
  Solve probability and expectation problems

  This set of problems evaluates probabilistic reasoning and expectation skills across discrete and continuous settings, covering conditional probability with evolving information, convolution and distribution derivation, occupancy/collector problems, symmetry-based variance on manifolds, and sequential selection/optimal stopping.

  Statistics & MathOnsite
• CitiMedium·Software Engineer
  Solve two logic brain teasers

  This pair of puzzles evaluates logical deduction and optimization competencies—one testing information-theoretic reasoning with constrained ternary comparisons and the other testing sequencing and scheduling trade-offs for minimal total time—and belongs to the Cognitive Ability / Logic category.

  Statistics & MathOnsite
• CoinbaseMedium·Data Scientist
  Calculate Conversion Lift CI

  This question tests the ability to derive and calculate a confidence interval for the difference in conversion rates between two groups, and to explain how this interval informs a business decision.

  Statistics & MathOnsiteStatisticsA/B TestingInference
• CoinbaseMedium·Data Scientist
  Calculate a Confidence Interval

  This question evaluates a candidate's competency in statistical inference for A/B testing, specifically the construction and interpretation of confidence intervals for differences in proportions, and falls under the Statistics & Math domain relevant to Data Scientist roles; it tests practical application (deriving point estimates and standard errors) alongside conceptual understanding (assumptions behind normal approximation versus exact, score-based, or bootstrap intervals). Interviewers commonly ask this to assess ability to quantify treatment effects, reason about approximation validity and alternative interval methods, and distinguish between absolute and relative lift when reporting experimental results.

  Statistics & MathOnsite
• DRWMedium·Data Scientist
  Compute Markov steady state and expectations

  Compute Markov steady state and expectations evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite
• DRWEasy·Data Scientist
  Derive eigenvalues and sum for inverse matrix

  Derive eigenvalues and sum for inverse matrix evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite
• DRWHard·Quantitative Researcher
  Expected Dart Score for a Bivariate Normal Throw with Ring Scoring

  Calculate the expected score of a dart throw modeled by a zero-mean bivariate normal distribution with circular scoring rings, calibrated using a known hit probability inside the inner ring.

  Statistics & MathOnsiteProbabilityBivariate NormalExpected Value
• DRWHard·Quantitative Researcher
  Expected Rounds Until a Shopping-Cart Line Empties Under Random Transfers

  Tests modeling discrete-time Markov chains, formulating hitting-time difference equations, and solving symmetric random walk absorption problems analytically.

  Statistics & MathOnsiteMarkov ChainsProbabilityRandom Walk
• DRWHard·Quantitative Researcher
  Expected Tosses Until HHT Given HHT Appears Before HTH

  Calculate the probability that the coin sequence HHT appears before HTH in repeated fair tosses, and find the conditional expected number of tosses until termination given that HHT appears first.

  Statistics & MathOnsiteprobabilitymarkov-chainsconditional-expectation
• DRWHard·Quantitative Researcher
  Expected Winnings in a Random-Walk Money Collection Game on 45 Stones

  Calculates a player's expected winnings in a random-walk money collection game on an odd-sized circle of stones using Gambler's Ruin and parity arguments.

  Statistics & MathOnsiteprobabilityrandom-walkgamblers-ruin
• DRWHard·Quantitative Researcher
  Posterior Probability of a Two-Headed Coin After Three Heads

  This question tests the application of Bayes' theorem, conditional likelihoods, and posterior probability updates given sequential binary observation data.

  Statistics & MathOnsiteProbabilityBayes' TheoremQuantitative Research
• DRWHard·Quantitative Researcher
  Probability the Two Strongest Teams Meet in a 16-Team Knockout Final

  Calculate the probability that the two highest-ranked teams face each other in the championship match of a 16-team single-elimination tournament with probabilistic match outcomes.

  Statistics & MathOnsiteprobabilitycombinatoricsconditioning
• DRWMedium·Data Scientist
  Solve Markov and distribution expectation problems

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Solve Markov and distribution expectation problems states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathOnsite