000			01749nam a2200193 4500
020			_a9783031631894
041			_aEnglish
082			_a330.0212 _bPAS/P
084			_2Colon Classification
100			_aPascucci, Andrea
245			_aProbability Theory I : _bRandom Variables and Distributions
250			_a1
260			_aItaly: _bSpringer, _c2024.
300			_a382p.
500			_aThis 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.
505			_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
650			_aEconomics- Probability Theory
942			_2ddc _cREF
999			_c748876 _d748876