Empirical model building : data, models, and reality / James R. Thompson.

Models of growth and decay -- Models of competition, survival, and combat -- Epidemics -- Bootstrapping -- Monte-Carlo solution of differential equations -- SIMEST, SMIDAT, and psuedoreality -- Exploratory data analysis -- Noise killing chaos -- Bayesian approaches -- Multivariate and robust procedures in statistical process control -- Optimization and estimation in the real (noisy) world -- Utility and group preference -- A primer in sampling -- Stock market: strategies based on data versus strategies based on ideology -- Appendix A. A brief Introduction to probability and statistics -- Appendix B. Statistical tables.

"This book presents a hands-on approach to the basic principles of empirical model building through the shrewd mixture of differential equations, computer-intensive methods, and data in a single-volume. It includes a series of real-world statistical problems illustrating modeling skills and techniques that are applicable to a broad range of audiences from applied statisticians to practicing MBAs. It covers models of growth and decay, systems where competition and interaction add to the complexity of the model, and discusses both classical and non-classical data analysis methods, alongside an extended list of more than twenty essential topics. The author also includes numerous exercises, an emphasis on computational finance and Bayesian techniques, and timely discussions of epidemics, quality control, and chaos in a dynamic world"--