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Autor(en): 
  • Guojun Gan
  • Computational Probability with Python: Theory, Simulation, and Actuarial Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (November 2026)  
    Genre:  Schulbücher 
     
    Wahrscheinlichkeitsrechnung und Statistik
    ISBN:  9781041354642 
    EAN-Code: 
    9781041354642 
    Verlag:  Taylor & Francis Ltd 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D  
    Seiten:  280 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:

    Probability theory provides the foundation for understanding uncertainty in fields ranging from finance and insurance to engineering and data science. This textbook is designed for undergraduate actuarial students seeking a clear, practical, and mathematically sound introduction to the subject. Requiring only a first course in calculus, it develops core ideas in a structured and accessible way, making it suitable for a one-semester course as well as for independent study.

    What sets this book apart is its balanced approach between intuition and rigor. Rather than relying heavily on measure-theoretic formalism or focusing solely on computational techniques, it introduces essential concepts-such as probability spaces-in a gradual and approachable manner. By combining theoretical development with computational tools, the text bridges the gap between abstract understanding and real-world application, preparing students for both academic study and professional practice.

    Key features:

    • A balanced presentation that introduces foundational concepts of probability without heavy measure-theoretic machinery
    • Clear, step-by-step development starting from set theory and building toward probability models and applications
    • Numerous practice questions adapted from Society of Actuaries Probability (P) exam materials
    • Selected solutions with detailed explanations to support self-study and deeper understanding
    • Integrated Python simulations in every section to illustrate concepts and verify results
    • Accompanying Jupyter notebooks available online for interactive learning and experimentation

    By combining mathematical rigor, practical exercises, and modern computational tools, this book offers a solid introduction to probability theory. It is ideal for actuarial students preparing for professional exams, while also serving as a valuable resource for students in related fields who seek a solid and engaging foundation in probability.

      



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