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Probability theory.. I,. Random variables and distributions

Record Type:	Electronic resources : Monograph/item
Title/Author:	Probability theory./ by Andrea Pascucci.
remainder title:	Random variables and distributions
Author:	Pascucci, Andrea.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xxi, 382 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	1 Measures and probability spaces -- 2 Random variables -- 3 Sequences of random variables -- 4 Conditional probability -- 5 Summary exercises -- Appendix A: Dynkin's theorems -- Appencix B: Absolute continuity -- Appendix C: Uniform integrability.
Contained By:	Springer Nature eBook
Subject:	Probabilities. -
Online resource:	https://doi.org/10.1007/978-3-031-63190-0
ISBN:	9783031631900

Probability theory.. I,. Random variables and distributions
Pascucci, Andrea.

Probability theory.I,Random variables and distributions[electronic resource] /Random variables and distributionsby Andrea Pascucci. - Cham :Springer Nature Switzerland :2024. - xxi, 382 p. :ill. (some col.), digital ;24 cm. - UNITEXT. La matematica per il 3+2,v. 1652038-5757 ;. - UNITEXT.La matematica per il 3+2 ;v. 165..

1 Measures and probability spaces -- 2 Random variables -- 3 Sequences of random variables -- 4 Conditional probability -- 5 Summary exercises -- Appendix A: Dynkin's theorems -- Appencix B: Absolute continuity -- Appendix C: Uniform integrability.

This book provides a concise yet rigorous introduction to probability theory. Among the possible approaches to the subject, the most modern approach based on measure theory has been chosen: although it requires a higher degree of mathematical abstraction and sophistication, it is essential to provide the foundations for the study of more advanced topics such as stochastic processes, stochastic differential calculus and statistical inference. The text originated from the teaching experience in probability and applied mathematics courses within the mathematics degree program at the University of Bologna; it is suitable for second- or third-year students in mathematics, physics, or other natural sciences, assuming multidimensional differential and integral calculus as a prerequisite. The four chapters cover the following topics: measures and probability spaces; random variables; sequences of random variables and limit theorems; and expectation and conditional distribution. The text includes a collection of solved exercises.

ISBN: 9783031631900

Standard No.: 10.1007/978-3-031-63190-0doiSubjects--Topical Terms:

518889
Probabilities.

LC Class. No.: QA273

Dewey Class. No.: 519.2

Probability theory.. I,. Random variables and distributions
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505 0 $a 1 Measures and probability spaces -- 2 Random variables -- 3 Sequences of random variables -- 4 Conditional probability -- 5 Summary exercises -- Appendix A: Dynkin's theorems -- Appencix B: Absolute continuity -- Appendix C: Uniform integrability.
520 $a This book provides a concise yet rigorous introduction to probability theory. Among the possible approaches to the subject, the most modern approach based on measure theory has been chosen: although it requires a higher degree of mathematical abstraction and sophistication, it is essential to provide the foundations for the study of more advanced topics such as stochastic processes, stochastic differential calculus and statistical inference. The text originated from the teaching experience in probability and applied mathematics courses within the mathematics degree program at the University of Bologna; it is suitable for second- or third-year students in mathematics, physics, or other natural sciences, assuming multidimensional differential and integral calculus as a prerequisite. The four chapters cover the following topics: measures and probability spaces; random variables; sequences of random variables and limit theorems; and expectation and conditional distribution. The text includes a collection of solved exercises.
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