Statistical Analysis of Cost-Effectiveness Data

for doing this, I still believe that this material will be helpful to students. The best chapter in this section is Chapter 5, in which the author gives a nice treatment of variance reduction techniques through sampling, stratified sampling, and importance sampling. The book’s third part consists of Chapter 6, in which material related to finance is introduced, including derivatives, various types of options, and the standard stochastic volatility model. The exposition is quite mathematical, and the linkage to simulation and the use of Maple is, unfortunately, sketchy. The last core segment, Chapters 7 and 8, covers random processes and then MCMC methods. Although I enjoyed the presentation of this material, I think that those trying to learn the subject would be frustrated by the tenuous connections to finance and the limited number of examples, the main one being the estimation of pump failure rates. One additional bonus chapter provides detailed computer solutions to the problems in earlier chapters, which I am sure will be greatly appreciated by readers. In summary, this book has some appealing features, but in my mind the failure to bridge the gap between finance applications and the simulation-random process material is a significant deficiency. It would take a masterful classroom instructor to overcome this problem; without such an effort, the untrained reader would be left with the impression that for finance and the probabilistic material, the twain have not yet met.