# Data Analysis

> Data analysis, statistical reasoning, quantitative insights, and numerical problem-solving

- Skill: `aizech/data-analysis` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add aizech/data-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/aizech/data-analysis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: aizech (https://skillmd.com/u/aizech)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/aizech/data-analysis

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# Data Analysis Skill

Use this skill when analyzing data, performing calculations, interpreting statistics, or solving quantitative problems.

## When to Use

- Performing calculations
- Interpreting statistical data
- Analyzing trends or patterns
- Comparing quantities
- Working with percentages, ratios
- Data-driven decision support

## Analysis Process

### 1. Understand the Question

- What is being asked?
- What data is available?
- What calculations are needed?
- What is the expected output?

### 2. Data Examination

- Identify relevant data points
- Check for missing values
- Verify units consistency
- Note any anomalies

### 3. Calculation/Analysis

Perform appropriate analysis:

- **Descriptive**: Mean, median, mode, range, std dev
- **Comparative**: Ratios, percentages, differences
- **Trend**: Growth rates, changes over time
- **Statistical**: Confidence intervals, significance

### 4. Interpretation

- Explain what results mean
- Put numbers in context
- Identify patterns/trends
- Note limitations or caveats

## Common Calculations

| Type | Formula | Use |
|------|---------|-----|
| Percentage | (part/whole) × 100 | Proportions |
| Growth Rate | ((new-old)/old) × 100 | Change over time |
| Average | Sum/Count | Central tendency |
| Ratio | a:b | Comparative |
| Probability | favorable/total | Likelihood |

## Best Practices

- Show your work/calculations
- Use appropriate precision
- Include units
- Verify calculations
- Note assumptions
- Provide context
- Highlight key insights
- Acknowledge limitations

## Presentation

Present results:

- Clearly and concisely
- With appropriate visualizations if helpful
- In context of the original question
- With caveats if needed