statistical-analysis Skill
Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results. Published by anthropics in knowledge-work-plugins.
What is statistical-analysis Skill?
Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results. Published by anthropics in knowledge-work-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Testing
- Data analysis
- Testing use cases
- Data analysis use cases
Technical details
- Install or run with Copy skill directory
When to use statistical-analysis Skill
- Use it for testing.
- Use it for data analysis.
Built with
Editorial notes
Source
- Creator: anthropics
- Repository: anthropics/knowledge-work-plugins
- Skill file: data/skills/statistical-analysis/SKILL.md
What it does
Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results.
Skill instructions
Statistical Analysis Skill Descriptive statistics, trend analysis, outlier detection, hypothesis testing, and guidance on when to be cautious about statistical claims. Descriptive Statistics Methodology Central Tendency Choose the right measure of center based on the data: | Situation | Use | Why | |---|---|---| | Symmetric distribution, no outliers | Mean | Most efficient estimator | | Skewed distribution | Median | Robust to outliers | | Categorical or ordinal data | Mode | Only option for non-numeric | | Highly skewed with outliers (e.g., revenue per user) | Median + mean | Report both; the gap shows skew | Always report mean and median together for business metrics. If they diverge significantly, the data is skewed and the mean alone is misleading. Spread and Variability - Standard deviation: How far values typically fall from the mean. Use with normally distributed data. - Interquartile range (IQR): Distance from p25 to p75. Robust to outliers. Use with skewed data. - Coefficient
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Frequently asked questions
What is statistical-analysis?
statistical-analysis is a open-source AI agent skill with Copy skill directory. Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing.
Who is statistical-analysis best for?
statistical-analysis is best for reusing agent instructions, scripts, and references, testing workflows, data analysis workflows.
How do I install statistical-analysis?
Install or run statistical-analysis using Copy skill directory. Check statistical-analysis for the latest setup command.
Is statistical-analysis actively maintained?
statistical-analysis may need a closer maintenance check before production use.
Auto-fetched from GitHub.
