Buch, Englisch, 281 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 446 g
An Introduction for Engineers
Buch, Englisch, 281 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 446 g
ISBN: 978-3-642-06346-6
Verlag: Springer
This book presents 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. The text is written for students who have studied elementary undergraduate courses in engineering mathematics, perhaps including a minor course in statistics. The focus is on statistical applications within the field of engineering risk and safety analysis. Coverage includes Bayesian methods. The knowledge of such tools facilitates the understanding of the role of probability in risk analysis and proper use of outputs given by software packages.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Industrielle Qualitätskontrolle
- Technische Wissenschaften Bauingenieurwesen Bauingenieurwesen
- Technische Wissenschaften Technik Allgemein Technische Zuverlässigkeit, Sicherheitstechnik
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Technische Wissenschaften Technik Allgemein Technik: Allgemeines
Weitere Infos & Material
Basic Probability.- Probabilities in Risk Analysis.- Distributions and Random Variables.- Fitting Distributions to Data – Classical Inference.- Conditional Distributions with Applications.- to Bayesian Inference.- Intensities and Poisson Models.- Failure Probabilities and Safety Indexes.- Estimation of Quantiles.- Design Loads and Extreme Values.
