# scitex-stats

> scitex-stats — scitex-ai-scitex-stats. Use this tool when you need to perform statistical testing and analysis on your data, solving problems such as hypothesis testing and effect size estimation. It provides 23 tests, effect sizes, and power analysis, accepting data inputs and producing statistical results as outputs. Ideal for use in research and data-driven projects, especially when integrated with git for version control and collaboration.

Canonical page: https://skillsregistry.net/skills/scitex-ai-scitex-stats  
JSON: https://api.skillsregistry.net/v1/skills/scitex-ai-scitex-stats

## Description

Statistical testing framework — 23 tests, effect sizes, power analysis

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** AGPL-3.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/scitex-ai/scitex-stats)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "scitex-ai-scitex-stats"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/scitex-ai-scitex-stats` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/scitex-ai-scitex-stats/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt