rigor
mrnh/rigor
Classical hypothesis testing, effect sizes, power and sample-size analysis and multiple-comparisons correction, returned as cited, assumption-checked answers.
- Local integrations
Installation, supported tools and required credentials are maintained by the project.
Project details
- GitHub stars
- 1
- Language
- Python
- License
- MIT
- Forks
- 0
- Latest release
- v0.5.01mo ago
- Activity
- updated 1mo ago
- Platforms listed
- macOS, Windows, Linux
- ai-agents
- hypothesis-testing
- mcp
- mcp-server
- model-context-protocol
- python
- statistics
First MCP server?Start with the basics
Create validated, maintainable data charts and dashboards with Vizro tools and templates.
Convert almost any file or web content into Markdown.
Interact with Jupyter.
Data quality evaluation with Dingo: run rule-based and LLM-based evaluations and list its rules and prompts.
Autonomous data exploration of CSV datasets with generated insights.
Interact with and control Jupyter Notebooks.
Forecasting and prediction with Chronulus AI agents.
Orchestrate hyperparameter search and other optimization tasks with Optuna.