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(Ebook) Introduction To Probability Theory: A First Course On The Measure-theoretic Approach (World Scientific Series On Probability Theory And Its Applications) by Moshayedi, Nima ISBN 9789811243363, 9789811246746, 9811246742, 9811243360, B09Z6JXBQL

  • SKU: EBN-54596566
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Instant download (eBook) Introduction To Probability Theory: A First Course On The Measure-theoretic Approach (World Scientific Series On Probability Theory And Its Applications) after payment.
Authors:Moshayedi, Nima
Pages:292 pages.
Year:2022
Editon:1
Publisher:WSPC
Language:english
File Size:5.33 MB
Format:pdf
ISBNS:9789811243363, 9789811246746, 9811246742, 9811243360, B09Z6JXBQL
Categories: Ebooks

Product desciption

(Ebook) Introduction To Probability Theory: A First Course On The Measure-theoretic Approach (World Scientific Series On Probability Theory And Its Applications) by Moshayedi, Nima ISBN 9789811243363, 9789811246746, 9811246742, 9811243360, B09Z6JXBQL

This book provides a first introduction to the methods of probability theory by using the modern and rigorous techniques of measure theory and functional analysis. It is geared for undergraduate students, mainly in mathematics and physics majors, but also for students from other subject areas such as economy, finance and engineering. It is an invaluable source, either for a parallel use to a related lecture or for its own purpose of learning it. The first part of the book gives a basic introduction to probability theory. It explains the notions of random events and random variables, probability measures, expectation values, distributions, characteristic functions, independence of random variables, as well as different types of convergence and limit theorems. The first part contains two chapters. The first chapter presents combinatorial aspects of probability theory, and the second chapter delves into the actual introduction to probability theory, which contains the modern probability language. The second part is devoted to some more sophisticated methods such as conditional expectations, martingales and Markov chains. These notions will be fairly accessible after reading the first part.
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