data-and-experimentation

What problem does it solve?

This Skill provides a comprehensive suite of tools for data science and experimentation, enabling users to design, execute, and analyze experiments, as well as perform advanced statistical analysis.

Core Features & Use Cases

• Experiment Design: Offers guidance on designing A/B tests, multivariate tests, and holdout tests, including sample size estimation and ICE scoring.
• Statistical Analysis: Provides tools for hypothesis testing, sample sizing, effect sizes, confidence intervals, and statistical significance.
• Machine Learning: Assists with building and evaluating prediction models using XGBoost, SHAP, MLflow, and causal inference techniques.
• LLM Evaluation: Offers a framework for evaluating LLMs through fixture-driven, judge-based, and regression-guarded approaches.
• Use Case: Imagine you want to run an A/B test to measure the impact of a new feature on user engagement. Use this Skill to design the test, estimate the sample size, analyze the results, and draw conclusions based on statistical significance and effect sizes.

Quick Start

Use the data-and-experimentation skill to design an A/B test for the new feature 'Feature X' on the 'User Engagement' metric.