Understand Propensity Score Matching in Business Analytics
Overview
This question evaluates understanding of propensity score matching as a causal inference technique and related competencies in estimating treatment effects from observational product data, assessing required assumptions for unbiased estimates, and measuring covariate balance; the domain tested is Statistics & Math for a Data Scientist role.
Walmart Labs
Aug 4, 2025, 10:55 AM
Data Scientist
Onsite
Statistics & Math
0
0
Propensity Score Matching (PSM) in Observational Product Data
Context
You work on a growth analytics team estimating causal effects (e.g., of a feature rollout or marketing campaign) using observational product data where randomized experiments are not available.
Questions
- What is Propensity Score Matching (PSM) and in which business situations would you apply it?
- List the assumptions required for PSM to yield unbiased causal estimates.
- How do you assess whether the matching achieved good covariate balance?
Solution
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