Design statistical methods, baselines, diagnostics, variants, and ablations that directly address a formal problem formulation.
Scanned 9/24/2026
npx -y skills add FOURTEEN1416/academic-agent-toolkit --skill statistical-method-design --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: statistical-method-design
description: >
Design statistical methods, baselines, diagnostics, variants, and ablations
that directly address a formal problem formulation.
metadata:
category: domain
trigger-keywords: "method proposal,estimator,algorithm,baseline,ablation,diagnostic,statistical method"
applicable-stages: "3,4,5,6,7,8"
priority: "1"
---
# Statistical Method Design
## Overview
Use this skill after formal problem formulation. The method should be a response
to the formal target and assumptions, not a generic collection of techniques.
## Required Method Proposal
For each method:
- Name
- Problem it solves
- Formula or algorithm
- Inputs and outputs
- Tuning parameters
- Required assumptions
- Diagnostics
- Expected failure modes
- Computational cost
- Relation to baselines
## Baselines and Ablations
Always define meaningful baselines:
- Classical or standard method
- Naive or unadjusted method
- Oracle or idealized reference when available
- Robust variant
- Ablation removing the key design feature
## Method-to-Claim Map
Every method must connect to at least one claim:
```yaml
method_to_claim_map:
proposed_method:
claims: [C1, C2]
expected_evidence: "lower risk under stress condition"
theory_target: "consistency under assumptions A1-A3"
```
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