statistical-analysis
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.
Profile →npx skills add majiayu000/claude-skill-registry --skill statistical-analysis-yongjianwan-agentskill --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 of variation (CV)**: StdDev / Mean. Use to compare variability across metrics with different scales. - **Range**: Max minus min. Sensitive to outliers but gives a quick sens
- Descriptive Statistics Methodology
- Central Tendency
- Spread and Variability
- Percentiles for Business Context
- Describing Distributions
- Trend Analysis and Forecasting
- Identifying Trends
- Seasonality Detection
- Forecasting (Simple Methods)
- Outlier and Anomaly Detection
- Statistical Methods
- Handling Outliers
- Time Series Anomaly Detection
- Hypothesis Testing Basics
What does the statistical-analysis skill do?
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 do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill statistical-analysis-yongjianwan-agentskill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.