Random Variables and Distributions Pascucci, Andrea. creator author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XXI, 382 p. 24 illus., 16 illus. in color. online resource. 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. 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. by Andrea Pascucci. Stochastic processes Mathematical physics Probabilities Econometrics Mathematics Stochastic Processes Theoretical, Mathematical and Computational Physics Probability Theory Quantitative Economics Mathematics QA274-274.9 9783031631900 https://doi.org/10.1007/978-3-031-63190-0 https://doi.org/10.1007/978-3-031-63190-0 241019 20251030113234.0 978-3-031-63190-0