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＜E-Book＞
From Elementary Probability to Stochastic Differential Equations with MAPLE® / by Sasha Cyganowski, Peter Kloeden, Jerzy Ombach
(Universitext. ISSN:21916675)

Edition	1st ed. 2002.
Publisher	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
Year	2002
Size	XVI, 310 p. 19 illus : online resource
Authors	*Cyganowski, Sasha author Kloeden, Peter author Ombach, Jerzy author SpringerLink (Online service)
Subjects	LCSH:Probabilities LCSH:Statistics  LCSH:Numerical analysis LCSH:Algorithms FREE:Probability Theory FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Numerical Analysis FREE:Algorithms
Notes	1 Probability Basics -- 2 Measure and Integral -- 3 Random Variables and Distributions -- 4 Parameters of Probability Distributions -- 5 A Tour of Important Distributions -- 6 Numerical Simulations and Statistical Inference -- 7 Stochastic Processes -- 8 Stochastic Calculus -- 9 Stochastic Differential Equations -- 10 Numerical Methods for SDEs -- Bibliographical Notes -- References The authors provide a fast introduction to probabilistic and statistical concepts necessary to understand the basic ideas and methods of stochastic differential equations. The book is based on measure theory which is introduced as smoothly as possible. It is intended for advanced undergraduate students or graduates, not necessarily in mathematics, providing an overview and intuitive background for more advanced studies as well as some practical skills in the use of MAPLE in the context of probability and its applications. Although this book contains definitions and theorems, it differs from conventional mathematics books in its use of MAPLE worksheets instead of formal proofs to enable the reader to gain an intuitive understanding of the ideas under consideration. As prerequisites the authors assume a familiarity with basic calculus and linear algebra, as well as with elementary ordinary differential equations and, in the final chapter, simple numerical methods for such ODEs. Although statistics is not systematically treated, they introduce statistical concepts such as sampling, estimators, hypothesis testing, confidence intervals, significance levels and p-values and use them in a large number of examples, problems and simulations HTTP:URL=https://doi.org/10.1007/978-3-642-56144-3

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