# Summary Statistics

> Compute and interpret descriptive statistics: central tendency, dispersion, shape, and confidence intervals. Goes beyond pandas .describe() with statistical interpretation and contextual meaning. Use when you need a thorough statistical summary of your data.

- **Type:** Skill
- **Install:** `agentstack add skill-ericwang915-data-scientist-skills-summary-statistics`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [ericwang915](https://agentstack.voostack.com/s/ericwang915)
- **Installs:** 0
- **Category:** [Data & Analytics](https://agentstack.voostack.com/c/data-and-analytics)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [ericwang915](https://github.com/ericwang915)
- **Source:** https://github.com/ericwang915/data-scientist-skills/tree/main/ds-exploratory-analysis/skills/summary-statistics

## Install

```sh
agentstack add skill-ericwang915-data-scientist-skills-summary-statistics
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Summary Statistics

## Purpose
Provide a comprehensive statistical summary with interpretation — not just numbers, but what they mean for your analysis.

## How It Works

### Step 1: Central Tendency
- Mean, median, mode — and which is most appropriate for this distribution
- Trimmed mean (robust to outliers)
- Weighted mean (if weights are provided)

### Step 2: Dispersion
- Standard deviation, variance, coefficient of variation
- IQR, range, MAD (Median Absolute Deviation)
- Confidence intervals for the mean (95% CI)

### Step 3: Shape
- Skewness (with interpretation: symmetric, right-skewed, left-skewed)
- Kurtosis (with interpretation: leptokurtic, mesokurtic, platykurtic)
- Normality tests: Shapiro-Wilk, D'Agostino-Pearson, Anderson-Darling

### Step 4: Percentiles & Distribution
- Full percentile breakdown (1, 5, 10, 25, 50, 75, 90, 95, 99)
- Five-number summary with box plot
- Distribution fitting: identify the best-fitting distribution

### Step 5: Group Comparisons (if applicable)
- Statistics by category or time period
- Effect sizes between groups (Cohen's d, Cliff's delta)
- Statistical significance of group differences

## Usage Examples

```
"Calculate summary statistics for the conversion_rate column,
grouped by marketing channel"
```

```
"Is this revenue data normally distributed? Which summary statistic
should I report — mean or median?"
```

## Output Format

- **Statistics Table**: Full descriptive statistics with 95% CIs
- **Interpretation**: Plain-language explanation of what the numbers mean
- **Distribution Assessment**: Normality test results with recommendation
- **Python Code**: Reproducible computation script

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [ericwang915](https://github.com/ericwang915)
- **Source:** [ericwang915/data-scientist-skills](https://github.com/ericwang915/data-scientist-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-ericwang915-data-scientist-skills-summary-statistics
- Seller: https://agentstack.voostack.com/s/ericwang915
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.