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Stochastic World [electronic resource] / by Sergey S. Stepanov.

By: Stepanov, Sergey S [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Mathematical Engineering: Publisher: Heidelberg : Springer International Publishing : Imprint: Springer, 2013Description: X, 339 p. 70 illus., 32 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319000718.Subject(s): Mathematics | Electronic data processing | Distribution (Probability theory) | Mathematical physics | Statistics | Mathematics | Probability Theory and Stochastic Processes | Numeric Computing | Mathematical Methods in Physics | Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth SciencesDDC classification: 519.2 Online resources: Click here to access online
Contents:
Random Events -- Stochastic Equations -- Mean Values -- Probabilities -- Stochastic Integrals -- Systems of Equations -- Stochastic Nature -- Stochastic Society -- Computer Modeling.
In: Springer eBooksSummary: This book is an introduction into stochastic processes for physicists, biologists and financial analysts. Using an informal approach, all the necessary mathematical tools and techniques are covered, including the stochastic differential equations, mean values, probability distribution functions, stochastic integration and numerical modeling. Numerous examples of practical applications of the stochastic mathematics are considered in detail, ranging from physics to the financial theory.  A reader with basic knowledge of the probability theory should have no difficulty in accessing the book content.
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Random Events -- Stochastic Equations -- Mean Values -- Probabilities -- Stochastic Integrals -- Systems of Equations -- Stochastic Nature -- Stochastic Society -- Computer Modeling.

This book is an introduction into stochastic processes for physicists, biologists and financial analysts. Using an informal approach, all the necessary mathematical tools and techniques are covered, including the stochastic differential equations, mean values, probability distribution functions, stochastic integration and numerical modeling. Numerous examples of practical applications of the stochastic mathematics are considered in detail, ranging from physics to the financial theory.  A reader with basic knowledge of the probability theory should have no difficulty in accessing the book content.

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