Data Analytics

knowledge skill

Performs statistical analysis and trend identification on structured datasets. Produces a summary report containing calculated metrics, correlation coefficients, and identified anomalies.

Worked examples

• {"input": {"dataset": "sales_q3.csv", "analysis_goal": "Monthly growth rate", "aggregation_level": "Month"}, "output": {"metrics": {"avg_growth": "4.2%", "total_revenue": "125000"}, "trends": ["Linear increase in September", "Dip in mid-August"], "outliers": ["Aug 14: $12k spike"]}}
• {"input": {"dataset": "user_churn.json", "analysis_goal": "Correlation between login frequency and churn", "aggregation_level": "User Segment"}, "output": {"metrics": {"pearson_correlation": "-0.68", "churn_rate": "12%"}, "trends": ["Churn increases when logins drop below 2/week"], "outliers": ["Segment B: High login, high churn"]}}

Input

• dataset: CSV/JSON data source
• analysis_goal: Specific metric or trend to identify
• aggregation_level: Timeframe or category for grouping

Output

• metrics: Key-value pairs of calculated statistics
• trends: List of observed directional changes
• outliers: List of data points exceeding standard deviation thresholds

Details

• Skill type: knowledge skill
• Safety level: safe_public_research
• Version: 1.0.0