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interquartile-range

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This project uses statistical analysis to detect fraudulent credit card transactions by examining patterns and anomalies in a dataset of 10,000 transactions, calculating averages, medians, frequencies, and identifying outliers to distinguish between legitimate and fraudulent activities.

  • Updated Aug 6, 2024
  • Jupyter Notebook

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