
Data Analytics Interview
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General Framework
Before Testing
Setting Metrics
Experiment Design
Randomization
Analyze Results
Button AB Test
Experiment Validity
P-value to a Layman
New UI Effect
General Framework
Let’s start with a general framework for A/B testing. In practice, an A/B test can be summarized into four steps.
Choose and characterize metrics to evaluate your experiments. What do you care about? How do you want to measure the effect?
Choose the significance level, power, the length of the test, and calculate the required sample size.
Implement the A/B test with control/treatment groups and run the test.
Analyze the results and draw valid conclusions
In the next few sections, we’ll dive into each step in full detail.
To frame our understanding, let’s say that we’re looking to design an experiment around different features of Interview Query.
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