Preface
The second edition was motivated by comments from several users and readers that the chapters on statistical inference and stochastic processes would benefit from substantial extensions. To accomplish such extensions, I decided to bring in Mikael Andersson, an old friend and colleague from graduate school. Being five days my junior, he brought a vigorous and youthful perspective to the task and I am very pleased with the outcome. Below, Mikael will outline the major changes and additions introduced in the second edition.
Peter Olofsson
San Antonio, Texas, 2011
The chapter on statistical inference has been extended, reorganized, and split into two new chapters. Chapter 6 introduces the principles and concepts behind standard methods of statistical inference in general, while the important case of normally distributed samples is treated separately in Chapter 7. This is a somewhat different structure compared to most other textbooks in statistics since common methods such as t tests and linear regression come rather late in the text. According to my experience, if methods based on normal samples are presented too early in a course, they tend to overshadow other approaches such as nonparametric and Bayesian methods and students become less aware that these alternatives exist.
New additions in Chapter 6 include consistency of point estimators, large sample theory, bootstrap simulation, multiple hypothesis testing, Fisher's exact test, Kolmogorov–Smirnov test and nonparametric ...
