Does it generate visuals for assumption checking?

Yes, the skill provides diagnostic plots such as Q-Q plots, residual plots, and histograms to visually verify normality, linearity, and homoscedasticity.

Can it help me determine my sample size?

Absolutely. It features a priori power analysis tools to calculate the required sample size based on your desired effect size, power, and alpha levels.

Does this skill support non-parametric tests?

Yes, it includes alternatives like Mann-Whitney U, Kruskal-Wallis, and Wilcoxon signed-rank tests for when data violates normality assumptions.

Is the reporting formatted for academic journals?

Yes, the skill is designed to output results in standard APA format, including the required degrees of freedom, p-values, and effect size metrics ready for publication.

Which Python libraries does this skill utilize?

It leverages industry-standard libraries including Scipy.stats, Statsmodels, Pingouin for user-friendly testing, and PyMC/ArviZ for Bayesian modeling.

Statistical Analysis Toolkit

Name: Statistical Analysis Toolkit
Author: pur3v4d3r

bypur3v4d3r

•

데이터 과학 및 ML

Performs comprehensive statistical testing, hypothesis verification, and APA-compliant reporting for academic and scientific research.

This skill empowers Claude to act as a specialized statistical consultant, guiding users through the end-to-step process of data analysis. It provides rigorous support for selecting the right tests, verifying statistical assumptions with diagnostic visualizations, and executing complex analyses ranging from standard t-tests and ANOVA to advanced Bayesian modeling and regression. Designed for academic research, it ensures results are interpreted correctly and reported according to professional APA standards, making it an essential tool for scientists, researchers, and data analysts who treat knowledge as code.

주요 기능

01Comprehensive effect size calculation and a priori power analysis

02Generation of publication-ready APA-style statistical reports

03Automated statistical assumption verification and diagnostic visualizations

04Advanced regression modeling and Bayesian statistical analysis with Bayes Factors

051 GitHub stars

06Support for hypothesis testing, including t-tests, ANOVA, and non-parametric alternatives

사용 사례

01Verifying data assumptions before performing complex inferential statistics

02Planning study sample sizes using power analysis and effect size estimates

03Analyzing experimental research data for academic publication

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pur3v4d3r/pur3-pkb-codebase statistical-analysis

For use in Claude.ai and ChatGPT

주요 기능

01Comprehensive effect size calculation and a priori power analysis

02Generation of publication-ready APA-style statistical reports

03Automated statistical assumption verification and diagnostic visualizations

04Advanced regression modeling and Bayesian statistical analysis with Bayes Factors

051 GitHub stars

06Support for hypothesis testing, including t-tests, ANOVA, and non-parametric alternatives

사용 사례

01Verifying data assumptions before performing complex inferential statistics

02Planning study sample sizes using power analysis and effect size estimates

03Analyzing experimental research data for academic publication

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pur3v4d3r/pur3-pkb-codebase statistical-analysis

For use in Claude.ai and ChatGPT