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Statistics & Math Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
- 9403
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- 546
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- 11
- Topics
- 8
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Showing 181–210 of 439 results
- LiftoffHardMachine Learning EngineerProbability That the Sum of 1,000 Fair Die Rolls Exceeds a Threshold
A fair six-sided die is rolled 1,000 times; estimate the probability that the sum of the faces exceeds a threshold, including a threshold of 600. Tests the mean and variance of one roll, how they scale for a sum of independent rolls, the normal approximation with a continuity correction, and range checks.
Statistics & MathOnsite - LinkedInEasyData ScientistChoose better bank queue and describe distributions
This question tests your ability to apply basic queueing theory to compare waiting times and your ability to reason about how distributional shape affects central tendency measures.
Statistics & MathTechnical ScreenQueueing TheoryProbabilityStatistics - LinkedInMediumData ScientistCompare queueing systems and common distributions
LinkedIn data scientist statistics screen covering pooled versus separate queues, height distributions and mixture distributions, right-skewed network degree, mean-median-mode ordering, and L1/L2 regularization bias.
Statistics & MathTechnical Screen - LinkedInMediumData ScientistDerive expectation for two consecutive heads
This question evaluates mastery of probability theory and stochastic processes, specifically expectation and variance calculations, Markov-chain or recurrence reasoning, and pattern waiting times in Bernoulli trials relevant for a Data Scientist role.
Statistics & MathTechnical Screen - LinkedInMediumData ScientistDerive mean and variance of x̄
This question tests your ability to derive the expected value and variance of the sample mean for a sequence of random variables, accounting for the effect of correlation between them.
Statistics & MathTechnical ScreenStatisticsVarianceExpectation - LinkedInMediumData ScientistEstimate an Experiment’s Mean Effect from Cohort and Metric Tables
Estimate experimental impact from cohort and timestamped metric data using user-level outcomes, difference in means, confidence intervals, and valid testing.
Statistics & MathOnsite - LinkedInHardData ScientistMeasure Causal Impact of Self-Selected App Redesign
LinkedIn causal inference prompt on measuring a self-selected app redesign, covering potential outcomes, ATT, propensity matching or weighting, staggered difference-in-differences, event studies, covariates, balance, and pre-trend validation.
Statistics & MathOnsite - LinkedInMediumMachine Learning EngineerTransform Biased and Uniform Random Bits Exactly
Tests the ability to design and mathematically prove exact random variate generators between biased and uniform bit sources, analyzing termination and expected sample complexity.
Statistics & MathTechnical ScreenProbabilityAlgorithmsSampling - LyftMediumData ScientistAnalyze Rider Behavior in Dynamic-Pricing Trial
Analyze Rider Behavior in Dynamic-Pricing Trial 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 & MathTechnical Screen - LyftMediumData ScientistCommuter Ride-Choice Probability: Committed and Permanent Riders
Tests discrete probability modeling, complementary counting, and Bayesian updating to analyze multi-day commuter behavior across distinct rider segments.
Statistics & MathTechnical Screenprobabilitybayes-theoremconditional-probability - LyftMediumData ScientistCompute Commuter Ride Probabilities
This question tests the ability to apply Bayes' Theorem and marginal probability to model commuter behavior and predict ride-hailing demand based on environmental factors.
Statistics & MathTechnical ScreenProbabilityBayesian InferenceConditional Probability - LyftMediumData ScientistCompute Poisson supply–demand match probability
This question evaluates understanding of probability distributions and stochastic modeling—specifically Poisson processes, the Skellam distribution for differences, expectation of minima, and probabilistic capacity planning within the Statistics & Math domain.
Statistics & MathOnsite - LyftEasyData ScientistDetermine Probability of Single Ride on Following Day
Evaluates a binomial probability setup for a ride-pricing experiment with two independent offers. Strong answers model the number of reasonable prices as Binomial(2, P), compute exactly one success as 2P(1-P), and compute permanent-rider probability as P squared.
Statistics & MathTechnical Screen - LyftEasyData ScientistExplain Bayes’ Theorem and P-Value in Decision-Making
Explain Bayes’ Theorem and P-Value in Decision-Making 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 & MathTechnical Screen - MathWorksMediumSoftware EngineerCalculate tiered cost and break-even
This question evaluates the ability to model tiered piecewise cost functions, compute total and average unit costs, and perform break-even analysis using basic algebra and arithmetic.
Statistics & MathOnline Assessment - MathWorksEasySoftware EngineerCompute probability of drawing reds
This question evaluates understanding of probability theory and combinatorics, specifically reasoning about sampling without replacement and calculating event probabilities using counting methods.
Statistics & MathOnline Assessment - MathWorksEasySoftware EngineerCompute urn-draw probabilities and expectations
This question evaluates understanding of elementary probability concepts—dependent events, conditional probability, and expected value—using an urn model with draws without replacement.
Statistics & MathOnline Assessment - MathWorksHardSoftware EngineerDeduce position from logic clues
This question evaluates the ability to model and reason about constraint-satisfaction on a 2D grid, including logical inference with directional and adjacency relations, combinatorial placement constraints, and determination of uniqueness.
Statistics & MathOnline Assessment - MathWorksEasySoftware EngineerDeduce row order from logic clues
This question evaluates logical deduction, constraint satisfaction, and basic combinatorial reasoning used to infer ordering from positional clues. Commonly asked to assess a candidate's ability to apply discrete math and spatial reasoning within the Statistics & Math domain, it targets conceptual understanding of constraints rather than practical implementation.
Statistics & MathOnline Assessment - MercorHardSoftware EngineerFind the Probability That One Shop Supplies the Top Two Coffees
Calculate the probability that the top-ranked coffees in a blind competition come from the same shop under an exchangeable, tie-free ranking model.
Statistics & MathTechnical Screenprobabilitycombinatoricsexchangeability - MercorMediumSoftware EngineerProbability Both Drinks from One Coffee Shop Outscore Both Drinks from Another
A probability brainteaser: two drinks are ordered at each of two coffee shops and every drink receives a quality score, and you must find the probability that both drinks from the first shop outscore both drinks from the second. It tests symmetry arguments, counting rankings, and stating independence and tie assumptions.
Statistics & MathTechnical Screen - MercorMediumSoftware EngineerProbability That One Customer's Two Coffees Beat Another's Two
A probability puzzle in which two customers each buy two cups of coffee of random quality, and you find the chance that one customer's cups are better than the other's. It tests clarifying what better means, using symmetry over rankings, checking the result a second way, and reasoning about ties and correlated cups.
Statistics & MathTechnical Screen - MercorMediumSoftware EngineerReason About Coffee-Quality Comparison Probabilities
Calculate conditional comparison probabilities for coffee quality scores under continuous and discrete distributions, accounting for ties and sample permutations.
Statistics & MathTechnical Screenprobabilitycombinatoricsstatistics - MetaMediumData ScientistAnalyze User Comment Distribution and Sampling Effects
Evaluates statistical reasoning about right-skewed user comment counts and sampling distributions. Strong answers place median, mean, and p95 correctly, then use the Central Limit Theorem to explain why group averages become less variable and more symmetric.
Statistics & MathOnsite - MetaMediumData ScientistAnalyze User Transfer Distribution in Initial Launch Period
Evaluates distribution analysis for transfer counts after a new P2P payments launch. Strong answers specify the denominator, describe zero inflation and right skew, locate mean, median, mode, and p95, and explain how adoption, cohorts, and exposure change the distribution over time.
Statistics & MathOnsite - MetaMediumData ScientistAnalyze ad targeting expectations and distributions
This question evaluates a data scientist's competency in probabilistic modeling, expected-value decision-making, variance decomposition for mixture distributions, and Poisson/exponential arrival-process analysis within the Statistics & Math domain.
Statistics & MathHR Screen - MetaMediumData ScientistAnalyze skewed comments and sampling effects
This question evaluates understanding of descriptive statistics for right‑skewed count data and inferential concepts such as sampling distributions, standard error, percentiles, and the Central Limit Theorem, and is commonly asked to probe how skewness and sample size affect central tendency measures and uncertainty in estimates.
Statistics & MathOnsite - MetaMediumData ScientistAnnotating and forecasting a long‑tail distribution
Evaluates robust summarization and forecasting for long-tailed daily share-count distributions. Strong answers compute mean, median, P1, P99, visualize with log scales or percentile bands, and forecast seasonality with heavy-tail-aware methods.
Statistics & MathOnsite - MetaHardData ScientistApply sequential testing without p-hacking
This question evaluates a candidate's competency in sequential hypothesis testing, alpha‑spending rules (Pocock vs O’Brien–Fleming), always‑valid inference methods such as mixture‑SPRT and e‑values, and strategies for controlling error rates across multiple metrics.
Statistics & MathOnsite - MetaMediumData ScientistCalculate Ad Insertion Statistics for Two Methods
Meta statistics prompt comparing two ad-insertion strategies, covering binomial moments, deterministic quotas, tail probability for excessive ads, adjacent ad pairs, and risk of long ad runs.
Statistics & MathOnsite
Liftoff
LinkedIn
Lyft
MathWorks
Mercor
Meta