This textbook integrates traditional statistical data analysis with new computational
experimentation capabilities and concepts of algorithmic complexity and chaotic behavior in
nonlinear dynamic systems. This was the first advanced text reference to bring together such a
comprehensive variety of tools for the study of random phenomena occurring in engineering and
the natural life and social sciences. The crucial computer experiments are conducted using
the readily available computer program Mathematica® Uncertain Virtual Worlds(TM) software
packages which optimize and facilitate the simulation environment. Brief tutorials are included
that explain how to use the Mathematica® programs for effective simulation and computer
experiments. Large and original real-life data sets are introduced and analyzed as a model for
independent study. This is an excellent classroom tool and self-study guide. The material is
presented in a clear and accessible style providing numerous exercises and bibliographical
notes suggesting further reading. Topics and Features Comprehensive and integrated treatment of
uncertainty arising in engineering and scientific phenomena - algorithmic complexity
statistical independence and nonlinear chaotic behavior Extensive exercise sets examples and
Mathematica® computer experiments that reinforce concepts and algorithmic methods Thorough
presentation of methods of data compression and representation Algorithmic approach to model
selection and design of experiments Large data sets and 13 Mathematica®-based Uncertain Virtual
Worlds(TM) programs and code This text is an excellent resource for all applied statisticians
engineers and scientists who need to use modern statistical analysis methods to investigate
and model their data. The present softcover reprint is designed to make this classic textbook
available to a wider audience.
