A/B Test Analysis Framework

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Analyze A/B test results with detailed reasoning.

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Analyze A/B test comparing {{variant_a}} vs {{variant_b}} for {{model}}.

Step 1: Validate test setup (sample sizes, randomization, duration)
Step 2: Calculate key metrics for each variant from {{metrics_data}}
Step 3: Perform statistical significance tests
Step 4: Check for confounding variables
Step 5: Estimate practical significance and business impact
Step 6: Make deployment recommendation with confidence level

Show calculations and reasoning throughout.

Details

Category

Analysis

Use Cases

A/B test analysisVariant comparisonStatistical evaluation

Works Best With

claude-opus-4.5gpt-5.2gemini-2.0-flash
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