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The research presents a tool for project cost modeling using statistical methods and Python libraries Pandas and NumPy. Key stages include data input, random number generation, statistical analysis, and result export to Excel. The study examines uniform distribution, calculates key indicators (mean, standard deviation, confidence intervals), and provides a flexible code structure for adaptation and expansion.

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Creating a Monte Carlo Distribution Simulation Program

  • 会议论文

  • 发表日期：

    2025年

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  • Sergey Masaev,
  • Alina Charikova,
  • Ksenia Ivanova

摘要

The research presents a tool for project cost modeling using statistical methods and Python libraries Pandas and NumPy. Key stages include data input, random number generation, statistical analysis, and result export to Excel. The study examines uniform distribution, calculates key indicators (mean, standard deviation, confidence intervals), and provides a flexible code structure for adaptation and expansion.