The present book is based on a course developed as partofthe large NSF-funded GatewayCoalitionInitiativeinEngineeringEducationwhichincludedCaseWest- ern Reserve University, Columbia University, Cooper Union, Drexel University, Florida International University, New Jersey Institute ofTechnology, Ohio State University, University ofPennsylvania, Polytechnic University, and Universityof South Carolina. The Coalition aimed to restructure the engineering curriculum by incorporating the latest technological innovations and tried to attract more and betterstudents to engineering and science. Draftsofthis textbookhave been used since 1992instatisticscoursestaughtatCWRU, IndianaUniversity, Bloomington, and at the universities in Gottingen, Germany, and Grenoble, France. Another purpose of this project was to develop a courseware that would take advantage ofthe Electronic Learning Environment created by CWRUnet-the all fiber-optic Case Western Reserve University computer network, and its ability to let students run Mathematica experiments and projects in their dormitory rooms, and interactpaperlessly with the instructor.
Theoretically,onecould try togothroughthisbook withoutdoing Mathematica experimentsonthecomputer,butitwouldbelikeplayingChopin's Piano Concerto in E-minor, or Pink Floyd's The Wall, on an accordion. One would get an idea ofwhatthe tune was without everexperiencing the full richness andpowerofthe entire composition, and the whole ambience would be miscued.
Rezensionen / Stimmen
"This is an innovative book... Well-constructed computer exercises with a bundled easily usable software package 'Mathematica® Uncertain Virtual Worlds®
'... 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 becomea classic." -Mathematical Reviews
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Research
Illustrationen
Maße
Höhe: 241 mm
Breite: 160 mm
Dicke: 34 mm
Gewicht
ISBN-13
978-0-8176-4031-6 (9780817640316)
DOI
10.1007/978-1-4612-2028-2
Schweitzer Klassifikation
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.
