Modern Mathematical Statistics

At one time, the term "statistics" was used simply to refer to a collection of numbers. Today, that collection is called data and "statistics" encompasses an ever-expanding science. This text covers this science in a clear and concise fashion, yet in enough detail to give readers a solid foundation in all aspects of the field. Treatment of each topic is thorough enough to make the coverage self-contained for a course in probability, and exceptional care has been taken to balance theory with applications. In addition to classical probability theory, such modern topics as order statistics and limiting distributions are discussed, along with applied examples from a wide variety of fields. Discussions include the core mathematical statistics topics of estimation, testing and confidence intervals; ranking and selection procedures; decision theory; nonparametric statistics; regression and ANOVA; and robust statistical procedures. Computer-assisted data analysis is discussed at several points, reflecting the importance of statistical computation to the field. FORTRAN programs and BMDP routines are included, as well as the highly popular SAI routines.
The potential contribution of expert systems to statistics is also examined.