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statistical-analysis

Select hypothesis tests, validate assumptions, and generate APA-style reporting.

Updated May 26, 2026
Search Tags:#hypothesis testing#statistics#power analysis#apa reporting#bayesian analysis#assumption checking#effect sizes
One-click install
npx skills add https://github.com/XWIlluDelu/agent-share --skill statistical-analysis-xwilludelu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: statistical-analysis
Source: https://github.com/XWIlluDelu/agent-share/tree/main/lib/statistical-analysis
Command: npx skills add https://github.com/XWIlluDelu/agent-share --skill statistical-analysis-xwilludelu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

It helps you select appropriate statistical tests, verify assumptions, run analyses, and produce publication-ready APA-style reporting without guesswork.

Core Features & Use Cases

  • Test selection & planning: Guides you through choosing tests for group comparisons, relationships, regression, and Bayesian alternatives, including multiple-comparison considerations and power planning.
  • Assumption checking & diagnostics: Performs normality, homogeneity of variance, outlier detection, and regression linearity checks with visual diagnostics and actionable recommendations.
  • Professional output: Produces interpretation-oriented results including effect sizes, confidence intervals, power/sensitivity guidance, and APA-formatted reporting.

Quick Start

Use the statistical-analysis skill to turn your dataset into an assumption-checked, effect-size-inclusive hypothesis test with an APA-ready results narrative for publication.

Frequently Asked Questions about statistical-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I choose the right hypothesis test for my dataset and research design?▼

Hypothesis test selection is guided through a structured decision workflow covering group comparisons, correlations, regression, and Bayesian alternatives based on your data structure and research questions.

Can I use this to check statistical assumptions like normality and variance before running tests?▼

Assumption checking is fully supported with normality tests, homogeneity of variance checks, outlier detection, and regression linearity diagnostics, including visual plots and actionable recommendations.

How do I report statistical results in APA format with effect sizes and confidence intervals?▼

APA reporting is generated automatically with interpretation-oriented outputs including effect sizes, confidence intervals, power guidance, and publication-ready results narratives for your hypothesis tests.

Does this support Bayesian analysis as an alternative to frequentist hypothesis testing?▼

Bayesian analysis alternatives are supported alongside frequentist and nonparametric tests, allowing you to select appropriate methodologies within the provided decision workflow for your statistical modeling.

What is power analysis and sensitivity analysis used for in statistical planning?▼

Power analysis and sensitivity analysis are integrated for statistical planning, helping determine required sample sizes and detectable effect sizes before running hypothesis tests to ensure robust study designs.

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