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Probability and Risk Analysis

An Introduction for Engineers

Springer Berlin,
96,25 € Lieferbar in 2-3 Tagen
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A textbook presenting notions and ideas at the foundations of a statistical treatment of risks. The text is unlike that found in traditional mathematics literature and differs from typical textbooks in its verbal approach to many explanations and examples.


Titel: Probability and Risk Analysis
Autoren/Herausgeber: Igor Rychlik, Jesper Rydén
Ausgabe: Softcover reprint of hardcover 1st ed. 2006

ISBN/EAN: 9783642063466

Seitenzahl: 281
Format: 23,5 x 15,5 cm
Produktform: Taschenbuch/Softcover
Gewicht: 450 g
Sprache: Englisch

The purpose of this book is to present concepts in a statistical treatment of risks. Such knowledge facilitates the understanding of the in?uence of random phenomena and gives a deeper knowledge of the possibilities o?ered by and algorithms found in certain software packages. Since Bayesian methods are frequently used in this ?eld, a reasonable proportion of the presentation is devoted to such techniques. The text is written with student in mind – a student who has studied - ementary undergraduate courses in engineering mathematics, may be incl- ing a minor course in statistics. Even though we use a style of presentation traditionally found in the math literature (including descriptions like de- itions, examples, etc.), emphasis is put on the understanding of the theory and methods presented; hence reasoning of an informal character is frequent. With respect to the contents (and its presentation), the idea has not been to write another textbook on elementary probability and statistics — there are plenty of such books — but to focus on applications within the ?eld of risk and safety analysis. Each chapter ends with a section on exercises; short solutions are given in appendix. Especially in the ?rst chapters, some exercises merely check basic concepts introduced, with no clearly attached application indicated. However, among the collection of exercises as a whole, the ambition has been to present problems of an applied character and to a great extent real data sets have been used when constructing the problems.

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