Probability Theory
General data
Course ID:  360MS21PRBa 
Erasmus code / ISCED: 
11.103

Course title:  Probability Theory 
Name in Polish:  Probability Theory 
Organizational unit:  Faculty of Mathematics 
Course groups: 
(in Polish) Erasmus+ sem. zimowy 
ECTS credit allocation (and other scores): 
6.00

Language:  English 
Type of course:  elective courses 
Prerequisites (description):  Mathematical Analysis III Combinatorics 
Mode:  Blended learning 
Short description: 
Field of science: natural science; discipline: mathematics We will discuss the mathematical formulation of basic probability theory, including random variables and the laws of large numbers. The limitations of the theory will motivate us to study measuretheoretic probability theory. 
Full description: 
Course profile: academic Form of study: stationary Course type: obligatory Field of science: natural science; Academic discipline: Mathematics Year: 2, semester: 3 Prerequisities: Mathematical Analysis III; Combinatorics lecture 30 h. exercise class 30 h. Verification methods: lectures, exercises, consultations, studying literature, home works, discussions in groups. ECTS credits: 6 Balance of student workload: attending lectures15x2h = 30h attending exercise classes 7x4h + 2h(preliminary teaching) = 30h preparation for classes 7x3h = 21h completing notes after exercises and lectures 7x2h = 14h consultations 5x2h = 10h the final examination: preparation.and take 15h + 4h = 19h Quantitative description Direct interaction with the teacher: 75 h., 3 ECTS Practical exercises: 75 h., 3 ECTS 
Learning outcomes: 
Has general knowledge of classical probabilistic problems, including the laws of large numbers and limit theorems for discrete random variables.KA6_WG03, KA6_WG07 Knows the concept and basic properties of probability.KA6_WG03, KA6_WG04, KA6_WG07, KA6_UW19 Knows basic probability calculation schemes, including Bernoulli's scheme.KA6_WG03, KA6_WG04, KA6_WG07, KA6_UO01 Is able to give examples of discrete and continuous probability distributions and discuss selected random experiments and the mathematical models in which these distributions occur.KA6_WG03, KA6_WG04, KA6_WG07, KA6_WG02, KA6_UW20, KA6_UO01, KA6_KO01 Is able to determine the basic parameters of the distribution of a random variable with a discrete and continuous distribution. KA6_WG03, KA6_WG04, KA6_WG07, KA6_WG02, KA6_UW21, KA6_UO01, KA6_KO01 Is able to build a probabilistic model for a given random event and indicate the method of calculating the probability. KA6_WG03, KA6_WG04, KA6_WG07, KA6_WG02, KA6_UW19, KA6_UO01, KA6_KO01 Is able to use the basic schemes of probability calculus, including the total probability formula and Bayes' formula.KA6_WG03, KA6_WG04,KA6_WG02, KA6_UO01, KA6_KO01 Is able to describe discrete random phenomena in the world around him, with the appropriate use of language and probabilistic concepts. KA6_WG02, KA6_UW19, KA6_UO01, KA6_KO01 Knows the limitations of one's own knowledge and understands the need for further education in the field of probability theory. KA6_KK01, KA6_KO01 
Assessment methods and assessment criteria: 
Examinations Graded exercises 
Classes in period "Academic year 2023/2024" (past)
Time span:  20231001  20240630 
Navigate to timetable
MO TU W TH WYK
CW
FR 
Type of class: 
Class, 30 hours
Lecture, 30 hours


Coordinators:  Tomasz Czyżycki, Andrew McKee, Aneta Sliżewska  
Group instructors:  Andrew McKee  
Students list:  (inaccessible to you)  
Examination: 
Course 
Examination
Class  Grading 

Bibliography: 
R Meester, A natural introduction to probability theory. Birkhäuser, 2008. Available online at https://link.springer.com/book/10.1007/9783034877862 (on campus). A N Shiryaev, Probability (second edition). Graduate Texts in Mathematics, volume 95. Springer, 1996. Available online at https://link.springer.com/book/10.1007/9781475725391 (on campus). T Cacoullos, Exercises in probability. Problem Books in Mathematics. SpringerVerlag, 1989. Available online at https://link.springer.com/book/10.1007/9781461245261 (on campus). 
Classes in period "Academic year 2024/2025" (future)
Time span:  20241001  20250630 
Navigate to timetable
MO TU W TH FR 
Type of class: 
Class, 30 hours
Lecture, 30 hours


Coordinators:  (unknown)  
Group instructors:  Andrew McKee  
Students list:  (inaccessible to you)  
Examination: 
Course 
Examination
Class  Grading 
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