Anbieter: HPB-Red, Dallas, TX, USA
Hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Sprache: Englisch
Verlag: Elsevier Science & Technology, 2014
ISBN 10: 0123948118 ISBN 13: 9780123948113
Anbieter: Better World Books, Mishawaka, IN, USA
Zustand: Fine. Used book that is in almost brand-new condition.
8vo Hardcover. Zustand: Very Good. 5th Edition. 670p. Contents are unmarked on white pages. Dark plum boards are glossy and pointed with minor shelf wear. Binding is tight with secure hinges. Supplements not included.
Anbieter: BookHolders, Towson, MD, USA
Zustand: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: fifth ] Publisher: Academic Press Pub Date: 8/28/2014 Binding: Hardcover Pages: 686 fifth edition.
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
EUR 72,49
Anzahl: 1 verfügbar
In den WarenkorbZustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1650grams, ISBN:9780123948113.
Anbieter: Toscana Books, AUSTIN, TX, USA
Hardcover. Zustand: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Introduction to Probability and Statistics for Engineers and Scientists, Fifth Edition is a proven text reference that provides a superior introduction to applied probability and statistics for engineering or science majors. The book lays emphasis in the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data from actual studies across life science, engineering, computing and business are incorporated in a wide variety of exercises and examples throughout the text. These examples and exercises are combined with updated problem sets and applications to connect probability theory to everyday statistical problems and situations. The book also contains end of chapter review material that highlights key ideas as well as the risks associated with practical application of the material. Furthermore, there are new additions to proofs in the estimation section as well as new coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions. This text is intended for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for scientists, engineers, and other professionals seeking a reference of foundational content and application to these fields. Clear exposition by a renowned expert authorReal data examples that use significant real data from actual studies across life science, engineering, computing and businessEnd of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer scienceNew additions to proofs in the estimation sectionNew coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions. 686 pp. Englisch.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Introduction to Probability and Statistics for Engineers and Scientists, Fifth Edition is a proven text reference that provides a superior introduction to applied probability and statistics for engineering or science majors. The book lays emphasis in the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data from actual studies across life science, engineering, computing and business are incorporated in a wide variety of exercises and examples throughout the text. These examples and exercises are combined with updated problem sets and applications to connect probability theory to everyday statistical problems and situations. The book also contains end of chapter review material that highlights key ideas as well as the risks associated with practical application of the material. Furthermore, there are new additions to proofs in the estimation section as well as new coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions. This text is intended for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for scientists, engineers, and other professionals seeking a reference of foundational content and application to these fields. Clear exposition by a renowned expert authorReal data examples that use significant real data from actual studies across life science, engineering, computing and businessEnd of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer scienceNew additions to proofs in the estimation sectionNew coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.