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Building a Modern Online Experimentation Platform with Streamlit (Part1)
- The article discusses the limitations of relying solely on p-values and Average Treatment Effect (ATE) in experimentation.
- An interactive platform using Streamlit is introduced to explore advanced experimentation techniques.
- The platform allows users to analyze data through various lenses to make strategic decisions.
- Classic A/B test results may be inconclusive based on p-values and confidence intervals.
- CUPED (Controlled-experiment Using Pre-Experiment Data) technique helps increase precision in detecting treatment effects.
- By applying CUPED, inconclusive results can turn into statistically significant wins without needing more data.
- Heterogeneous Treatment Effects (HTE) analysis explores how treatment effects vary among different user groups.
- Using logistic regression models, HTE analysis can identify specific user segments that respond differently to treatments.
- The article emphasizes the importance of using multiple analytical lenses to make data-driven decisions.
- The interactive platform encourages rigorous experimentation and helps in making informed business decisions.
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