Data Investigation & Narrative Builder
Turn raw data into compelling, verified data-driven stories
What You Can Do
This skill analyzes your datasets to uncover statistically significant patterns and newsworthy insights automatically. It validates claims against your data, structures findings into compelling narratives that connect evidence to context, and generates verification frameworks so readers can trust your conclusions. You get publication-ready data stories backed by rigorous statistical analysis and transparent methodology.
Features
Identifies statistically significant outliers, trends, correlations, and anomalies that form the core of your story
Applies significance tests, confidence intervals, and correlation analysis to verify claims and eliminate spurious patterns
Organizes raw findings into compelling story arcs with headline, context, evidence, and implications
Generates transparent methodology documentation and checklists that readers can use to audit your analysis
Rates each claim by statistical strength, sample size, effect size, and methodological rigor
Flags unexpected data points and generates hypotheses for investigating potential stories
Connects your findings to industry benchmarks, historical trends, and background information for impact
Example Output
Example 1: Investigation Report
Tech Company Pay Gap Widens in 2024
Key Finding
Female engineers at surveyed tech companies earn 12% less than male counterparts at the same level (p < 0.001), the widest gap since 2020.
Evidence
- Sample: 2,847 salary records across 45 companies
- Median female engineer: $185K | Median male engineer: $210K
- Controlled for experience and role: 7% gap remains (statistically significant)
- 89% of companies show gender-based disparity
Confidence Score: 4.2/5
- Statistical significance: Excellent (p < 0.001)
- Sample diversity: Good (45 companies, multiple levels)
- Potential bias: Limited (self-reported data)
Example 2: Trend Analysis
Your remote work dataset shows adoption peaked at 48% in Q2 2024, then declined to 38% by Q3. Analysis reveals this pattern is driven by tech sector consolidation and RTO mandates, not broader market economic shifts.
What's Included
- Pattern Discovery Engine: Automatically scans structured data to detect trends, outliers, and relationships worth investigating
- Statistical Test Suite: Applies significance tests, correlation analysis, t-tests, and anomaly detection to validate claims
- Narrative Template: Structures findings into publication-ready story format with headline, evidence, and implications
- Verification Methodology: Provides transparent documentation of analysis approach and checklists for independent audit
- Evidence Scorecard: Generates confidence ratings for each finding based on statistical rigor and data quality
Who It's For
- Data Journalists
- Investigative Reporters
- Research Analysts
- Impact Storytellers
- Market Researchers
Best For
- Data-driven investigative journalism and feature stories
- Statistical claim verification and fact-checking
- Converting raw datasets into narrative-driven reports
- Publishing research findings with confidence scores
- Auditing data analysis methodology for rigor and transparency
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