feat(analytics): add statistics and reporting modules#4
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Implements comprehensive statistical analysis capabilities: - Two-sample t-test (Welch's) for model comparison - Mann-Whitney U test for non-parametric analysis - Linear trend analysis for time series - A/B testing framework for model version comparison - Bootstrap confidence intervals for uncertainty estimation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implements automated report generation for stakeholders: - RegionalMetrics dataclass for environmental KPIs - ImpactReport with carbon, validation, and recommendations - ReportGenerator for JSON and HTML report output - Trend analysis integration for year-over-year comparisons - Actionable recommendations based on threshold analysis Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Updates module __init__.py to expose complete public API: - Carbon estimation: CarbonEstimator, estimate_carbon - Validation: GroundTruthValidator, validate_predictions - Statistics: t_test, mann_whitney, trend_analysis, ab_test - Reporting: ReportGenerator, generate_report Enables clean imports like: from climatevision.analytics import estimate_carbon, generate_report Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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May 17, 2026
…tics-statistics Merging Francis's analytics statistics and reporting modules
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Summary
Changes
src/climatevision/analytics/statistics.py: Statistical testing (t-test, Mann-Whitney, trend analysis)src/climatevision/analytics/reporting.py: Impact report generation (JSON/HTML)src/climatevision/analytics/__init__.py: Updated module exportsTest plan
from climatevision.analytics import generate_reportAuthor: Francis Umo (@franchaise)
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