Computational Probability with Python (el. knyga) (skaityta knyga) | knygos.lt

Aprašymas

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.