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 Technical Screen rounds at Meta.

What role is this question designed for?

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

Implement Clustered Sampling to Mitigate Network Effects in Testing

Quick Overview

This question evaluates a candidate's ability to design clustered randomization strategies to address interference and spillovers in networked experiments, testing competencies in causal inference, experimental design, and statistical reasoning within Analytics & Experimentation.

Scenario

You are planning an A/B test for a new recommendation algorithm in a networked product where users interact with friends and creators. Because user outcomes can be affected by others' assignments (network spillovers), standard individual randomization may violate the "no-interference" assumption.

Task

Design a clustered random sampling approach to select test and control users that limits interference.

Questions

How would you construct clusters and assign treatment/control at the cluster level?
Which clustering choices make sense in this context (e.g., markets, friend/interaction graphs), and why do they reduce interference?
What trade-offs or risks does clustered sampling introduce (e.g., intracluster correlation and power loss)?

Hints

Consider geographic/language markets and social/interaction graphs.
Aim to minimize cross-cluster ties that carry spillovers.
Intracluster correlation (ICC) inflates variance; anticipate power loss.
Think about analysis with cluster-robust methods and stratification.

Quick Overview

Questions

How would you construct clusters and assign treatment/control at the cluster level?

Which clustering choices make sense in this context (e.g., markets, friend/interaction graphs), and why do they reduce interference?

What trade-offs or risks does clustered sampling introduce (e.g., intracluster correlation and power loss)?

Implement Clustered Sampling to Mitigate Network Effects in Testing

Quick Overview

Scenario

Task

Questions

Hints

Solution

Comments (0)

Implement Clustered Sampling to Mitigate Network Effects in Testing

Quick Overview

Scenario

Task

Questions

Hints

Solution

Comments (0)