Statistical Analysis Guide
Overview
This skill guides the agent through proper statistical hypothesis testing, ensuring normality checks, appropriate test selection, effect size reporting, and multiple comparison corrections.
When to Use
Use this skill when the user wants to:
- Compare two or more groups statistically
- Test a hypothesis about differences or relationships
- Determine if an observed effect is statistically significant
Decision Tree
IF comparing two groups:
IF data is normal (Shapiro-Wilk p > 0.05) AND variances are equal:
→ Use independent samples t-test
ELIF data is normal but variances unequal:
→ Use Welch's t-test
ELSE (data is non-normal):
→ Use Mann-Whitney U test
→ Consider bootstrap confidence intervals
IF comparing 3+ groups:
IF data is normal AND variances are homogeneous:
→ Use one-way ANOVA with post-hoc (Tukey HSD)
ELSE:
→ Use Kruskal-Wallis test
→ Post-hoc: Dunn's test with Bonferroni correction
Guardrails
- REFUSE to report only p-values. Always include effect size (Cohen's d, eta-squared, or odds ratio) and confidence intervals.
- REFUSE to approve an experiment without power analysis showing power ≥ 80%.
- WARN if multiple comparisons are performed without correction (Bonferroni, Benjamini-Hochberg, or Holm).
- MUST NOT claim statistical significance without reporting the full context.
Output Format
Always report results in this structure:
Test: [test name]
Effect Size: [metric] = [value] ([interpretation])
95% CI: [lower, upper]
p-value: [value] (adjusted: [method])
Power: [value]
Assumptions checked: [list]
Edge Cases
- Small samples (n < 30): Use exact tests or bootstrap methods
- Tied data: Use appropriate tie-correction for rank-based tests
- What if normality is borderline?: Report both parametric and non-parametric results
Common Mistakes
- Using paired tests for independent samples (anti-pattern)
- Reporting "trending toward significance" for p = 0.06 (do not use for this)
- Cherry-picking seeds for reproducibility — report mean ± std across multiple seeds
Escape Hatch
Experienced users can override guardrails by explicitly stating: "I acknowledge [specific guardrail] and am proceeding because [justification]."
References
For detailed method guides, see the references/ directory.