# Statistical Reporting

Statistical test selection, assumption checking, and APA-formatted reporting.

- Repository: https://github.com/aiming-lab/AutoResearchClaw (14798 stars)
- Category: Testing
- License: MIT
- Last updated: 2026-08-19
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add aiming-lab/AutoResearchClaw --skill statistical-reporting -g -a claude-code -y`
Codex: `npx skills add aiming-lab/AutoResearchClaw --skill statistical-reporting -g -a codex -y`
Cursor: `npx skills add aiming-lab/AutoResearchClaw --skill statistical-reporting -g -a cursor -y`
Gemini CLI: `npx skills add aiming-lab/AutoResearchClaw --skill statistical-reporting -g -a gemini-cli -y`

## Description

Statistical test selection, assumption checking, and APA-formatted reporting. Use when analyzing experimental results or writing results sections.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## Statistical Reporting Best Practice

### Test Selection Quick Reference
1. **Comparing two groups (independent, normal)**: Independent t-test
2. **Comparing two groups (independent, non-normal)**: Mann-Whitney U test
3. **Comparing two groups (paired, normal)**: Paired t-test
4. **Comparing two groups (paired, non-normal)**: Wilcoxon signed-rank test
5. **Comparing 3+ groups (independent, normal)**: One-way ANOVA + post-hoc
6. **Comparing 3+ groups (non-normal)**: Kruskal-Wallis test
7. **Relationship between continuous variables**: Pearson or Spearman correlation
8. **Categorical outcomes**: Chi-square or Fisher's exact test
9. **Predicting continuous outcome**: Linear regression
10. **Predicting binary outcome**: Logistic regression

### Assumption Checking
1. **Normality**: Shapiro-Wilk test (n < 50) or visual Q-Q plots
2. **Homogeneity of variance**: Levene's test before t-tests and ANOVA
3. **Independence**: Verify study design ensures independent observations
4. **Linearity**: Scatter plots and residual plots for regression
5. **Multicollinearity**: VIF < 5 for multiple regression predictors
6. When assumptions are violated, use non-parametric alternatives or robust methods

### APA Reporting Format
1. **t-test**: t(df) = X.XX, p = .XXX, d = X.XX
2. **ANOVA**: F(df_between, df_within) = X.XX, p = .XXX, eta-squared = .XX
3. **Correlation**: r(df) = .XX, p = .XXX [95% CI: .XX, .XX]
4. **Chi-square**: chi-square(df, N = XXX) = X.XX, p = .XXX
5. **Regression**: beta = X.XX, SE = X.XX, t = X.XX, p = .XXX
6. Always report exact p-values (not "p < .05") unless p < .001
7. Use leading zero for values that can exceed 1 (e.g., t = 0.50) but not for those bounded by 1 (e.g., p = .032, r = .45)

The rest: https://github.com/aiming-lab/AutoResearchClaw/blob/HEAD/.claude/skills/statistical-reporting/SKILL.md