Probability theory II

General data

Course ID:	1000-115aRP2a
Erasmus code / ISCED:	11.103 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0541) Mathematics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Probability theory II
Name in Polish:	Rachunek prawdopodobieństwa II (potok I)
Organizational unit:	Faculty of Mathematics, Informatics, and Mechanics
Course groups:	Obligatory courses for 4th grade JSIM (3I+4M)
ECTS credit allocation (and other scores):	(not available) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Type of course:	obligatory courses
Prerequisites:	Probability theory I 1000-114aRP1a
Short description:	The course contains an introduction to the convergence theory for probability distributions (equivalence of various definitions, Central Limit Theorem) and to applications of harmonical analysis in the theory (properties of characteristic functions). Moreover, some elements of martingale theory and Markov chains will be discussed.
Full description:	Convergence of probability distributions. The characteristic function of a probability distribution, applications to computing moments and distributions of sums of independent random variables. The uniqueness theorem. Levy's theorem stating that the convergence of probability distributions can be described in terms of the pointwise convergence of their characteristic functions. The Central Limit Theorem. Introduction to the theory of martingales ("fair games"). Stopping moments. Doob's "optional sampling" theorem. Markov chains, ergodicity.
Bibliography:	(in Polish) J. Jakubowski i R. Sztencel, Wstęp do teorii prawdopodobieństwa, SCRIPT, Warszawa 2001. P. Billingsley, Prawdopodobieństwo i miara, PWN, Warszawa 1987. W. Feller, Wstęp do rachunku prawdopodobieństwa (t. I i II), PWN, Warszawa 1975 i późniejsze wydania. A. Borowkow, Rachunek prawdopodobieństwa, PWN, Warszawa 1975. S. Zubrzycki, Wykłady z rachunku prawdopodobieństwa i statystyki matematycznej, PWN, Warszawa 1970. A. Sziriajew, Wierojatnost, Nauka, Moskwa 1980.

This course is not currently offered.

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Copyright by University of Warsaw.