This text rigorously examines the fundamental principles and methodologies underlying stochastic simulation, preparing readers for its application in both research and practice. The book provides a comprehensive treatment of modeling, programming, and analysis of simulation experiments, grounding the reader in the core concepts of why simulation techniques are effective. It integrates object-oriented programming concepts for simulation and offers a thorough exploration of both the probabilistic and statistical underpinnings, ensuring accessibility by including all necessary background material. The work emphasizes lasting principles and provides specific training in modeling, programming, and analysis, distinguishing itself by preparing readers for simulation research.

The book is presented as a graduate-level text that offers a rigorous yet accessible treatment of stochastic simulation. Its emphasis on foundational principles and preparation for research distinguishes it from other texts that may focus more on algorithms. The approach aims to equip readers with a deep understanding of simulation's mechanics and its effective application in diverse fields. The content is structured to provide both theoretical grounding and practical skills in modeling, programming, and analysis.