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Probability Calculus I

General data

Course ID:	360-MS1-3RP1a
Erasmus code / ISCED:	11.102 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 Calculus I
Name in Polish:	Probability Calculus I
Organizational unit:	Faculty of Mathematics
Course groups:
ECTS credit allocation (and other scores):	4.00 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:	English
Type of course:	obligatory courses
Short description:	Assumptions and aims: After completing the course, the student should understand and be able to apply probabilistic methods.
Full description:	(in Polish) Academic discipline: science and natural science, field of study in the arts and science: mathematics
Bibliography:	1. D. Stirzaker - Prabability and Random variables. A beginner's Guide. 2. W. Feller - An Introduction to Probability Theory and Its Applications 3. G. Grimmet, D. Stirzaker - One Thousand Exercises in Probability.
Learning outcomes:	Student - has general knowledge of classical probabilistic theory, including the laws of large numbers and limit theorems for discrete random variables. - knows the concept and basic properties of probability. - knows the basic schemes of probability calculus, including sequence of Bernoulli trials. -can give examples of discrete and continuous probability distributions and discuss selected random experiments and mathematical models in which these distributions occur. - knows how to apply basic probability calculus schemes, including the formula for total probability and the Bayesian formula. - is able to describe discrete random phenomena in the world around him, along with the proper use of language and probabilistic concepts.
Assessment methods and assessment criteria:	exam

Classes in period "Academic year 2022/2023" (past)

Time span:	2022-10-01 - 2023-06-30	Selected timetable range: weekly course term Navigate to timetable MO TU WYK CW W TH FR
Type of class:	Class, 30 hours more information Lecture, 30 hours more information
Coordinators:	Tomasz Czyżycki, Urszula Ostaszewska, Aneta Sliżewska
Group instructors:	Urszula Ostaszewska
Students list:	(inaccessible to you)
Examination:	Course - Examination Class - Grading

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