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.
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.
Zusammenfassung
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.
Inhaltsverzeichnis
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.
