statistical-reporting

name	statistical-reporting
description	Statistical test selection, assumption checking, and APA-formatted reporting. Use when analyzing experimental results or writing results sections.
metadata	{"category":"writing","trigger-keywords":"statistic,hypothesis test,p-value,regression,ANOVA,t-test,effect size,confidence interval","applicable-stages":"14,17","priority":"3","version":"1.0","author":"researchclaw","references":"adapted from K-Dense-AI/claude-scientific-skills"}

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