$npx skillfedfor your agent

Statistical Analysis

Statistical Analysis guides researchers through rigorous interpretation of cardiology trial data, from selecting appropriate statistical tests to reporting effect sizes and confidence intervals. It covers test selection for different data types, explains p-values and their limits, and provides APA-style reporting templates with real trial examples.

Statistical Analysis teaches you how to select the right statistical test and properly interpret cardiology research findings.

AI-generated summary based on this skill's SKILL.md

5 3 unlicensed, metadata onlyupdated by drshailesh88

Decision gist · record as of 2026-06-18

Statistical Analysis teaches you how to select the right statistical test and properly interpret cardiology research findings. Statistical Analysis guides researchers through rigorous interpretation of cardiology trial data, from selecting appropriate statistical tests to reporting effect sizes and confidence intervals. It covers test selection for different data types, explains p-values and their limits, and provides APA-style reporting templates with real trial examples.

manual: git clone https://github.com/drshailesh88/integrated_content_OS → cp -r integrated_content_OS ~/.claude/skills/statistical-analysis

Use it when

  • Statistical Analysis guides you through the complete process: first identify your data type and research question.
  • Statistical Analysis covers a range of statistical methods including test selection for different data types, hypothesis testing procedures.
Same gist for agents: .md · .json

Install

drshailesh88/integrated_content_OS/statistical-analysis · repository language: Python

generated, unverified - the skill's exact subdirectory could not be determined; check the repository on GitHub

Open directory. Skills are indexed for reading, not audited. Review a skill's body before installing it.

Frequently asked questions

AI-generated answers based on this skill's SKILL.md and metadata

What is Statistical Analysis and what can it help me do?

Statistical Analysis is a comprehensive guide for rigorous interpretation of research data. It helps you select appropriate statistical tests for different data types, understand p-values and their limitations, report effect sizes and confidence intervals, and format results in APA style. The skill covers test selection, hypothesis validation, and includes real trial examples to support your analysis workflow.

How do I perform statistical analysis on my dataset?

Statistical Analysis guides you through the complete process: first identify your data type and research question, then select the appropriate statistical test using the skill's decision framework. The skill explains how to interpret results, calculate effect sizes and confidence intervals, and report findings in APA format. Real trial examples demonstrate each step of the analysis workflow.

What statistical methods and techniques does this skill cover?

Statistical Analysis covers a range of statistical methods including test selection for different data types, hypothesis testing procedures, p-value interpretation, effect size calculation, and confidence interval reporting. The skill explains the limitations of p-values and provides guidance on selecting tests appropriate to your research design and data characteristics.

Can Statistical Analysis help me with statistical testing?

Yes, Statistical Analysis specializes in statistical testing for hypothesis validation. It guides you through selecting the right test for your data, understanding what p-values mean and their limitations, calculating effect sizes, and reporting results with confidence intervals. The skill includes APA-style reporting templates and real trial examples to support your testing process.

How do I analyze and interpret numerical data effectively?

Statistical Analysis teaches you to interpret numerical data by first understanding your data type and research question. The skill explains how to select appropriate tests, calculate and report effect sizes and confidence intervals, and avoid common p-value misinterpretations. Real cardiology trial examples demonstrate practical interpretation of statistical results.

What statistical computation assistance does this skill provide?

Statistical Analysis provides computational support through guidance on test selection, effect size calculation, confidence interval computation, and result interpretation. While the skill focuses on methodology and interpretation rather than raw calculations, it equips you with the knowledge to perform or verify statistical computations and report them correctly in APA format.

Let your AI agent find skills like this

Example. Real query, live index.

You found this page by searching. An agent finds it by wishing: SkillFed indexes 56,283 agent skills by what they can do, searchable in plain language.

wish › “Perform statistical analysis on datasets”

Give your agent the search over MCP, or paste the wish link into any chat. No install? Search from any chat →

Related skills

statistical-analysis
by K-Dense-AI · K-Dense-AI/scientific-agent-skills

Conduct rigorous statistical tests—t-tests, ANOVA, chi-square, correlation, regression, and Bayesian methods—with systematic assumption verification and effect size reporting. The skill walks you through test selection, data inspection, assumption diagnostics, and APA-style write-ups so your analysis withstands peer review.

MITupdated Jul 2026
★ 31,940repo stars
tooluniverse-meta-analysis
by mims-harvard · mims-harvard/ToolUniverse

Combine quantitative results from two or more studies into a pooled estimate and confidence interval, with built-in heterogeneity assessment (I², Q, τ²). The skill converts raw reported values—odds ratios, risk ratios, hazard ratios, means, proportions, correlations—into the standardized (effect, standard error) format pooling requires, then applies fixed- or random-effects models and generates a forest plot to visualize agreement across studies.

Apache-2.0updated Jul 2026
★ 1,595repo stars
statistics
by beita6969 · beita6969/ScienceClaw

This skill guides you through test selection for continuous, categorical, and time-to-event data across different study designs. It includes assumption verification methods, multiple comparison corrections, and effect size benchmarks to ensure rigorous analysis. Follow integrated reporting standards to communicate results with full transparency.

MITupdated Jun 2026
★ 869repo stars
Statistical Analysis
by jaechang-hits · jaechang-hits/SciAgent-Skills

Statistical Analysis guides you through test selection, assumption verification, and effect size reporting for academic research. It covers frequentist methods like t-tests, ANOVA, and regression alongside Bayesian approaches, with specialized workflows for survival analysis, count models, and reliability assessment.

no license declared → metadata onlyupdated Jul 2026
★ 284repo stars
Carousel Copy
by drshailesh88 · drshailesh88/integrated_content_OS

Carousel Copy transforms research and clinical knowledge into slide-ready content that sounds like a specialist explaining to an informed audience. It guides you through voice calibration, compression techniques, and slide-type patterns—from hooks to CTAs—ensuring each frame delivers one clear idea backed by data and delivered with authority.

no license declared → metadata onlyupdated Jun 2026
★ 5repo stars
statistical-analysis
by winstonkoh87 · winstonkoh87/Athena-Public

This skill provides a structured five-step pipeline for delivering publication-ready statistical analyses. It guides you through data auditing, assumption validation, test execution with effect sizes, interpretation, and client-ready reporting in APA format across SPSS, R, and Python.

MITupdated Jul 2026
★ 554repo stars

More skills statistical-testing (MIT)

Tags
data-analyticsquantitative-methodsstatistical-testinghypothesis-validationdescriptive-statsinference-modelingnumeric-computation