Hypothesis Sage is a powerful command-line interface (CLI) tool designed to assist with statistical analysis and hypothesis testing. It leverages advanced language models and a curated database of statistical information to provide intelligent recommendations and explanations for various statistical scenarios.

We use Typer to create a simple CLI to access each tool, in addition to an agent that can answer complex questions.

In the future, we plan to create a web interface for access to Hypothesis Sage.

1. Query Database: Retrieve relevant statistical information from a curated database.
2. Generate Test Examples: Create detailed examples of how to apply specific statistical tests to given situations.
3. Find Best Test: Recommend appropriate statistical tests for a given scenario, including assumptions and their validity.
4. Explain Concepts: Provide explanations for statistical concepts and queries.
5. AI-Powered Assistance: Utilize an intelligent agent to answer complex statistical questions and provide comprehensive guidance.

Hypothesis Sage offers several commands to assist with your statistical analysis:

Here are some example uses of Hypothesis Sage:

1. Query the database:

   python hsage_cli.py query "What is the difference between Type I and Type II errors?"
   

2. Generate a test example:

   python hsage_cli.py make-example "t-test" "Comparing mean heights of two groups"
   

3. Find the best test for a scenario:

   python hsage_cli.py find-best-test "I want to compare the effectiveness of three different teaching methods on student test scores"
   

4. Explain a statistical concept:

   python hsage_cli.py explain-this "What is the central limit theorem?"
   

5. Ask a complex question:

   python hsage_cli.py ask "How do I interpret the results of a multiple regression analysis with interaction terms?"
   

These commands will provide you with detailed information, examples, and guidance for your statistical analysis needs.