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---
name: statistical-theory-analysis
description: >
Analyze theoretical properties of statistical methods under the formal
formulation: identifiability, bias, variance, consistency, asymptotics,
coverage, error bounds, robustness, and limitations.
metadata:
category: domain
trigger-keywords: "theory,proof,consistency,asymptotic normality,bias,variance,coverage,error bound,identifiability,robustness"
applicable-stages: "4,5,6,7,8,9,10"
priority: "1"
---
# Statistical Theory Analysis
## Overview
Use this skill after method proposal and before final experimental comparison.
Theory is required as a stage even if the final output is a simulation paper.
## Theory Outputs
Depending on the topic, provide:
- Identifiability argument
- Bias or variance calculation
- Consistency statement
- Asymptotic distribution
- Coverage or calibration argument
- Risk or error bound
- Robustness analysis
- Sensitivity or impossibility result
- Counterexample showing failure outside assumptions
## Theorem Template
```markdown
## Proposition
Under assumptions A1-Ak, method M satisfies ...
## Proof Sketch
1. ...
2. ...
3. ...
## Interpretation
This predicts that ...
## Limitations
The result does not cover ...
```
## Experimental Predictions
Every theoretical claim should produce an empirical prediction when possible:
- Direction of metric change
- Condition under which the method should improve
- Stress condition under which it should fail
- Baseline it should outperform