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goodness-of-fit

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A statistical analysis of the AI4I 2020 Predictive Maintenance dataset applying Reliability Theory. This project analyzes machine tool wear (Time-To-Failure) using Python, featuring distribution fitting, MLE/UMVUE parameter estimation, Kolmogorov-Smirnov goodness-of-fit testing, and the calculation of core reliability functions.

  • Updated Apr 21, 2026
  • Jupyter Notebook

End-to-End Python scalable forensic accounting toolkit implementing Benford's Law analysis for FTSE financial data. Delivers automated anomaly detection with Chi-Squared/MAD testing, comprehensive validation pipelines, and risk-based prioritization of investigative resources. Replicates Ausloos et al.'s (2025) methodology with full reproducibility.

  • Updated Sep 13, 2025
  • Jupyter Notebook

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