"This is an innovative book... Well-constructed computer exercises with a bundled easily usable software package 'Mathematica(R) Uncertain Virtual Worlds(R)'... The bibliographical notes that accompany each chapter...are clearly written with a keen eye toward encouraging students to enrich their understanding by pursuing additional reading...A lucidly written text and many well-designed computer experiments that enable students to simulate the whole process of some dynamic systems." -Technometrics "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 become a classic." -Mathematical Reviews

• I Descriptive Statistics-Compressing Data.- 1 Why One Needs to Analyze Data.- 2 Data Representation and Compression.- 3 Analytic Representation of Random Experimental Data.- II Modeling Uncertainty.- 4 Algorithmic Complexity and Random Strings.- 5 Statistical Independence and Kolmogorov’s Probability Theory.- 6 Chaos in Dynamical Systems: How Uncertainty Arises in Scientific and Engineering Phenomena.- III Model Specification-Design of Experiments.- 7 General Principles of Statistical Analysis.- 8 Statistical Inference for Normal Populations.- 9 Analysis of Variance.- A Uncertainty Principle in Signal Processing and Quantum Mechanics.- B Fuzzy Systems and Logic.- C A Critique of Pure Reason.- D The Remarkable Bernoulli Family.- F Tables.

"This is an innovative book... Well-constructed computer exercises with a bundled easily usable software package 'Mathematica(R) Uncertain Virtual Worlds(R)'... The bibliographical notes that accompany each chapter...are clearly written with a keen eye toward encouraging students to enrich their understanding by pursuing additional reading...A lucidly written text and many well-designed computer experiments that enable students to simulate the whole process of some dynamic systems." -Technometrics "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 become a classic." -Mathematical Reviews

• I Descriptive Statistics-Compressing Data.- 1 Why One Needs to Analyze Data.- 2 Data Representation and Compression.- 3 Analytic Representation of Random Experimental Data.- II Modeling Uncertainty.- 4 Algorithmic Complexity and Random Strings.- 5 Statistical Independence and Kolmogorov’s Probability Theory.- 6 Chaos in Dynamical Systems: How Uncertainty Arises in Scientific and Engineering Phenomena.- III Model Specification-Design of Experiments.- 7 General Principles of Statistical Analysis.- 8 Statistical Inference for Normal Populations.- 9 Analysis of Variance.- A Uncertainty Principle in Signal Processing and Quantum Mechanics.- B Fuzzy Systems and Logic.- C A Critique of Pure Reason.- D The Remarkable Bernoulli Family.- F Tables.