Replete with easy-to-understand examples ranging from the prediction of home runs in baseball using an hierarchical
Bayesian statistics model to estimating the expected return at blackjack using control variables, this text functions as a complete
consideration of simulation. Sheldon Ross provides broad yet thorough coverage of the subject, presenting the development of
a simulation study to analyze models, and demonstrates that by using random variables and the concept of discrete events, it is
possible to generate the behavior of a stochastic model over time. Also discussed are questions concerning when to stop a
simulation, how much confidence can be placed in the results, and extensive new information on the presentation of the alias
method for generating discrete random variables material not found in any other text. Students, practitioners, and researchers
alike will find this text to have an important place in their research libraries.