statistical-analysis

Choosing the right statistical test depends on your data type and study design. This skill provides method selection guidance for t-tests, ANOVA, regression, and nonparametric options, matching the appropriate statistical method to your specific research workflow.

Yes, you can generate APA format tables and narrative results. The skill produces APA and AMA-compliant reports, creating journal-ready manuscripts with properly formatted statistical tables and narrative summaries directly from your quantitative analysis.

Sample size and power analysis are calculated using integrated Python workflows with scipy, statsmodels, and pingouin, alongside R support. The skill computes statistical power and required sample sizes to ensure your research design meets deterministic analysis requirements.

Yes, the skill provides explicit guidance for avoiding p-hacking and statistical misinterpretation. It enforces robust reporting standards and deterministic workflows to prevent common errors in hypothesis testing and quantitative data analysis across disciplines.

Running ANOVA with post-hoc comparisons and effect sizes is handled through the skill's integrated analysis workflows. It processes multi-group experimental designs, calculating post-hoc tests and effect sizes while formatting the results into compliant reports.