Probability Theory
A.Y. 2018/2019
Learning objectives
Probability theory is now applied in a variety of fields including physics, engineering, biology, economics, social sciences, ... This course is an introduction to the rigorous theory of probability. The perspective theme is the Doob's theory of discrete time martingales. The Kolmogorov strong law of large numbers and the theorem of three series are proved with martingale techniques. In addition, the central limit theorem is proved together with the main results on week convergence and characteristic functions. In the part of exercises, the first results of Markov chains are introduced.
Expected learning outcomes
Knowledge of the topics of the course and their application to theoretical problems.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
Part I. Foundations:
Measure spaces
Events
Random variables
Independence
Integration
Expectation
Strong law of large numbers
Product measure
Gaussian vectors
Part II. Martingale Theory:
Conditional expectation
Martingales
The convergence theorem
UI Maringales, L1 convergence and applications
L2 Maringales, angle-brackets process and relation with martingale' convergence
Part III. Compendia of theory
Markov chains
Weak convergence. Tightness. Lévy's Convergence Theorem.
Central Limit Theorem
Measure spaces
Events
Random variables
Independence
Integration
Expectation
Strong law of large numbers
Product measure
Gaussian vectors
Part II. Martingale Theory:
Conditional expectation
Martingales
The convergence theorem
UI Maringales, L1 convergence and applications
L2 Maringales, angle-brackets process and relation with martingale' convergence
Part III. Compendia of theory
Markov chains
Weak convergence. Tightness. Lévy's Convergence Theorem.
Central Limit Theorem
MAT/06 - PROBABILITY AND STATISTICS - University credits: 9
Practicals: 30 hours
Lessons: 42 hours
Lessons: 42 hours
Professors:
Aletti Giacomo, Ugolini Stefania
Professor(s)
Reception:
on appointment
office 2099
Reception:
Please write an email
Room of the teacher or online room