- 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
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"Highly data-oriented, with an unusually large collection of real-life examples taken from industry and various scientific disciplines... The book departs from the standard fare, by [also] including detailed coverage of such contemporary topics as chaotic dynamical systems, the nature of randomness, computability and Kolmogorov complexity, encryption, ergodicity, entropy, and even fractals." -Short Book Reviews (Int'l Statistical Institute)
"The novelty of the book is the integration of ideas about statistics of random phenomena stemming from algorithmic computational complexity, classical probability theory and chaotic behavior in nonlinear systems, and the broad use of Mathematica in the exposition. Moreover, the examples of statistical problems used arise in real-life industrial and scientific lab situations and have been collected from the engineering and scientific literature, or through direct interaction with practicing engineers and scientists. The authors' goal is to give engineering and science students a forward-looking alternative to the usual introductory statistics courses...In summary, I find Introductory statistics and random phenomena an excellent textbook, and I strongly recommend it as an introductory technical statistics course to engineering and science students who have had a basic programming course in computer science. I expect it to becomea classic." -Mathematical Reviews