An intelligent recommendation engine that guides developers and researchers in selecting the most appropriate statistical methods for their datasets.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install statistical-analysis-advisor
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install statistical-analysis-advisor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Statistical Analysis Advisor?
The Statistical Analysis Advisor is a robust technical tool within the Openclaw Skills ecosystem designed to bridge the gap between raw data and valid scientific insights. It acts as a decision-support system, helping users navigate complex statistical choices—such as choosing between a T-test and ANOVA—by evaluating data types, distributions, and research objectives.
By utilizing this skill, teams can ensure their data analysis tasks maintain high standards of reproducibility and rigor. The tool emphasizes a structured execution path, providing documented fallback paths for missing inputs and explicit assumption tracking to safeguard the integrity of the final results.
Statistical Analysis Advisor Use Cases
- Selecting between parametric and non-parametric tests based on data distribution.
- Conducting assumption checks like Shapiro-Wilk for normality or Levene's test for variance homogeneity.
- Estimating required sample sizes and effect sizes (Cohen's d, eta-squared) for research planning.
- Validating experimental designs to ensure the chosen statistical method aligns with the number of groups and independence of samples.
How Statistical Analysis Advisor Works
- The user provides objectives and data characteristics such as data type, group count, and distribution info.
- The advisor validates the input against documented scope and identifies any missing critical parameters.
- The skill executes the packaged logic via scripts/main.py to process the decision tree.
- It generates a structured recommendation including the suggested test, underlying assumptions, and potential risks.
- The final output is delivered as a reproducible artifact, clearly separating deliverables from unresolved items.
Statistical Analysis Advisor Setup
To get started with this component of Openclaw Skills, ensure you have Python 3.10+ installed. Follow these steps to initialize the environment:
# Navigate to the skill directory
cd "scientific-skills/Data Analytics/statistical-analysis-advisor"
# Install required dependencies
pip install -r requirements.txt
# Verify the script entry point
python -m py_compile scripts/main.py
# View available command-line options
python scripts/main.py --help
Statistical Analysis Advisor Data Schema & Taxonomy
The skill organizes its operations through a structured hierarchy of scripts and reference materials:
| Component | Type | Description |
|---|---|---|
scripts/main.py |
Python Script | The primary execution engine and entry point. |
references/ |
Directory | Contains markdown guides for tests, assumptions, and power analysis. |
requirements.txt |
Config File | Lists Python dependencies like dataclasses and enum. |
CONFIG Block |
Code | In-file parameters for fixed settings and scope filters. |
Statistical Analysis Advisor Advanced Features
- Multi-stage decision tree logic for complex comparative analysis.
- Automated power analysis including post-hoc calculations.
- Built-in outlier detection guidance and independence verification.
- Integration-ready Python API for embedding the advisor into larger automated data pipelines.
- Extensible reference framework for adding domain-specific statistical constraints.
SKILL.md
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