Instruction: Outline an experimental design that minimizes bias and ensures robust causal conclusions.
Context: This question evaluates the candidate's expertise in experimental design, particularly in a tech product environment, ensuring clear isolation of the causal impact of new features.
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Firstly, my approach to designing this experiment would rely on a randomized controlled trial (RCT), the gold standard for causal inference. This method allows us to directly measure the effect of new feature updates on app engagement by comparing outcomes between a treatment group that experiences the new features and a control group that does not.
Step 1: Define the Outcome Variable Before launching the experiment, it's crucial to clearly define what we mean by 'app engagement.' For this context, let's consider 'daily active users' (DAU) as our primary metric. DAU is calculated as the number of unique users who logged on at least once on our platforms during a calendar day. This metric effectively captures user engagement and will serve as our outcome variable....