| name | regression-analyzer |
| description | Skill for comprehensive regression analysis and modeling |
| allowed-tools | ["Bash","Read","Write"] |
| metadata | {"specialization":"scientific-discovery","domain":"science","category":"Data Analysis","skill-id":"SK-SCIDISC-019"} |
| graph | {"domains":["domain:scientific-discovery"],"specializations":["specialization:scientific-research-methods"],"skillAreas":["skill-area:data-analysis","skill-area:statistical-analysis","skill-area:deep-web-research"],"workflows":["workflow:experiment-design","workflow:peer-review-cycle"],"roles":["role:research-engineer","role:computational-scientist"]} |
Regression Analyzer Skill
Purpose
Perform comprehensive regression analyses including model fitting, diagnostics, and interpretation for scientific data.
Capabilities
- Fit linear models
- Build generalized models
- Perform diagnostics
- Handle multicollinearity
- Generate predictions
- Interpret coefficients
Usage Guidelines
- Prepare data
- Specify model
- Fit regression
- Run diagnostics
- Refine if needed
- Interpret results
Process Integration
Works within scientific discovery workflows for:
- Relationship modeling
- Prediction generation
- Effect estimation
- Variable selection
Configuration
- Model specifications
- Diagnostic tests
- Variable selection
- Output formatting
Output Artifacts
- Model summaries
- Diagnostic plots
- Coefficient tables
- Prediction outputs