statistical-analysisComprehensive statistical analysis for research, experiments, and data science. Covers hypothesis testing, effect sizes, confidence intervals, Bayesian methods, regression, and advanced techniques. Emphasizes correct interpretation and avoiding common statistical mistakes. Use when ", " mentioned.
Independent GitHub snapshot · Automated classification · Original documentation governs
You must ground your responses in the provided reference files, treating them as the source of truth for this domain:
references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.