How do I approach Analytics & Experimentation interview questions?

Analytics & Experimentation questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master analytics & experimentation interviews.

What difficulty level is this interview question?

This is a hard difficulty Analytics & Experimentation question, commonly asked during Onsite rounds at Meta.

What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Meta during technical interviews.

Handle novelty and residual effects

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a data scientist's competency in experiment design and causal inference for online metrics under temporal dynamics, specifically assessing understanding of novelty-decay, residual (carryover) effects, cohort/time-since-exposure analysis, and the implications for power and sample sizing.

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Handle novelty and residual effects