Choose tests under non‑normal, unequal variance

Quick Overview

This question evaluates understanding of statistical inference for heavy‑tailed, heteroskedastic A/B test metrics, covering CLT conditions for t‑tests, variance‑robust tests, nonparametric and resampling approaches, log transformations and back‑transformation interpretation, and handling zero inflation within the Statistics & Math domain for Data Scientist roles. It is commonly asked because real‑world experimental metrics violate parametric assumptions, so interviewers probe both conceptual understanding of asymptotics and test assumptions and practical application of resampling, transformation, and two‑part modeling choices along with appropriate robustness checks.

Choose tests under non‑normal, unequal variance

Company: Instacart

Role: Data Scientist

Category: Statistics & Math

Difficulty: hard

Interview Round: Onsite

Quick Answer: This question evaluates understanding of statistical inference for heavy‑tailed, heteroskedastic A/B test metrics, covering CLT conditions for t‑tests, variance‑robust tests, nonparametric and resampling approaches, log transformations and back‑transformation interpretation, and handling zero inflation within the Statistics & Math domain for Data Scientist roles. It is commonly asked because real‑world experimental metrics violate parametric assumptions, so interviewers probe both conceptual understanding of asymptotics and test assumptions and practical application of resampling, transformation, and two‑part modeling choices along with appropriate robustness checks.

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Oct 13, 2025, 9:49 PM
hardData ScientistOnsiteStatistics & Math
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