Introduction to Probability and Stochastic Processes with Applications  PDF & ePUB Download
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 eBook:Introduction to Probability and Stochastic Processes with Applications
 Author:Liliana Blanco Casta?eda, Viswanathan Arunachalam, Selvamuthu Dharmaraja
 Edition:1 edition
 Categories:
 Data:20120626
 ISBN:1118294408
 ISBN13:9781118294406
 Language:English
 Pages:614
 Format:PDF
Description of Introduction to Probability and Stochastic Processes with Applications ebook
Introduction to Probability and Stochastic Processes with Applications presents a clear, easytounderstand treatment of probability and stochastic processes, providing readers with a solid foundation they can build upon throughout their careers. With an emphasis on applications in engineering, applied sciences, business and finance, statistics, mathematics, and operations research, the book features numerous realworld examples that illustrate how random phenomena occur in nature and how to use probabilistic techniques to accurately model these phenomena.
The authors discuss a broad range of topics, from the basic concepts of probability to advanced topics for further study, including It? integrals, martingales, and sigma algebras. Additional topical coverage includes:
 Distributions of discrete and continuous random variables frequently used in applications
 Random vectors, conditional probability, expectation, and multivariate normal distributions
 The laws of large numbers, limit theorems, and convergence of sequences of random variables
 Stochastic processes and related applications, particularly in queueing systems
 Financial mathematics, including pricing methods such as riskneutral valuation and the BlackScholes formula

Content
2. Random Variables and Their Distributions
3. Some Discrete Distributions
4. Some Continuous Distributions
5. Random Vectors
6. Conditional Expectation
7. Multivariate Normal Distributions
8. Limit Theorems
9. Introduction to Stochastic Processes
10. Introduction to Queueing Models
11. Stochastic Calculus
12. Introduction to Mathematical Finance
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