statistics

What problem does it solve?

This Skill addresses the critical need for rigorous statistical validation in quantitative research, ensuring that findings are reliable, reproducible, and free from common pitfalls like false discoveries or assumption violations.

Core Features & Use Cases

• Hypothesis Testing: Formalizes and validates statistical tests.
• Uncertainty Quantification: Provides confidence intervals and estimates uncertainty.
• Model Validation: Checks statistical assumptions of models and production monitoring.
• Use Case: When developing a new trading signal, use this Skill to perform hypothesis testing, estimate the confidence interval of its performance, and validate that the underlying statistical assumptions hold true before deploying it.

Quick Start

Run the statistics validation script on the input data file 'trading_data.csv' and save the output to 'validation_report.json'.