You are a Senior Data Scientist for a gaming platform such as PlayStation.
Answer the following experimentation questions.
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A/A test validation:
The experimentation platform ran an A/A test to validate randomization and logging. The intended split was 50% control and 50% treatment, but the observed assignment ratio was 51% control and 49% treatment.
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Is this a problem?
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How would you test whether the imbalance is statistically meaningful?
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What root causes would you investigate before trusting future A/B test results?
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Experiment design with social network effects:
The product team wants to launch a new feature that lets friends send virtual gifts to each other. The hypothesis is that gifting will increase user engagement.
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Define the primary metric, guardrail metrics, and success criteria.
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How would you design an experiment to estimate the feature's causal impact?
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What randomization unit would you choose: user-level, friend-cluster-level, region-level, or something else?
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How would your design change if users' friendship graph is highly connected, such that almost every user is connected directly or indirectly to almost every other user?
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What biases or validity threats would you worry about?