Localized reading guide
statistical-analysisPurpose, usage and source
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.
Source retrieved:
- Source repository
- anthropics/knowledge-work-plugins
- SKILL.md
data/skills/statistical-analysis/SKILL.md- Repository stars
- 34,049
- Repository updated
- 2026-10-30
- Categories
- Development
- Last collected
License: License file needs review
Workflow excerpts are reading aids, not executable instructions from Codez. No third-party Skill was run to produce this page.
The purpose and workflow passages below are upstream material, organized and translated for reading. They are distinct from the separately labeled Codez editorial analysis.
What this Skill 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.
How the upstream workflow works
When to Use
Use hypothesis testing when you need to determine whether an observed difference is likely real or could be due to random chance. Common scenarios: A/B test results: Is variant B actually better than A? Before/after comparison: Did the product change actually move the metric? Segment comparison: Do enterprise customers really have higher retention?
Upstream passage · L157 ↗Statistical Analysis Skill
Descriptive statistics, trend analysis, outlier detection, hypothesis testing, and guidance on when to be cautious about statistical claims.
Upstream passage · L7 ↗Central Tendency
Choose the right measure of center based on the data: Always report mean and median together for business metrics. If they diverge significantly, the data is skewed and the mean alone is misleading.
Upstream passage · L13 ↗p1: Bottom 1% (floor / minimum typical value)
p5: Low end of normal range
p25: First quartile
p50: Median (typical user)
p75: Third quartile
p90: Top 10% / power users
p95: High end of normal range
p99: Top 1% / extreme usersRequirements and setup
No short requirements passage was selected from this file. This does not mean the Skill has no dependencies. Check the repository setup instructions and referenced files.
Limits and quality checks
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Read further in the source
- Statistical Analysis Skill
- Central Tendency
- Spread and Variability
- Percentiles for Business Context
- Describing Distributions
- Identifying Trends
- Seasonality Detection
- Forecasting (Simple Methods)
- Statistical Methods
- Handling Outliers
- Time Series Anomaly Detection
- When to Use
- The Framework
- Practical Significance vs. Statistical Significance
- Sample Size Considerations
- Correlation Is Not Causation
- Multiple Comparisons Problem
- Simpson's Paradox
- Survivorship Bias
- Ecological Fallacy
- Anchoring on Specific Numbers
Related Skills
Translation and scope
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- Source retrieved
- Source commit
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91a15cfc144efffcd622b09827362a73993a3ff30e3a78114801832477c9f8a0