Probability Calculus I
General data
| Course ID: | 0600-MS1-3RP1#a | Erasmus code / ISCED: |
11.103
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(0541) Mathematics
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| Course title: | Probability Calculus I | Name in Polish: | Probability Calculus I |
| Department: | Faculty of Mathematics and Informatics | ||
| Course groups: |
(in Polish) 3L stac. I st. studia matematyki - przedmioty obowiązkowe |
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| ECTS credit allocation (and other scores): |
4.00  view allocation of credits |
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| Language: | English | ||
| Type of course: | obligatory courses |
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| Prerequisites: | Combinatorics 0600-MS1-1KOM#a |
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| Short description: |
Course objectives: By the end of the course the student should understand fundamental concept of probability and be able to use probabilistic methods in practice. |
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| Full description: |
Course profile: academic Form of study: stationary Course type: obligatory Academic discipline: Mathematics, field of study in the arts and science: mathematics Year: 3, semester: 5 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: 4 Balance of student workload: attending lectures15x2h = 30h attending exercise classes 7x4h + 2h(preliminary instructions) = 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: 74 h., 2 ECTS Practical exercises: 75 h., 3 ECTS |
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| Learning outcomes: |
Learning outcomes: Student has basic knowledge about problems of classical probability such that the low of large number and limit theorems.K_W04, K_W05 Student knows the concept of probability and its basic properties.K_W05, K_W12 Student knows basic probability schemes, including Bernoulli's scheme.K_W03, K_W05 Student is able to give examples of discrete and continuous probability distributions and discuss selected random experiments and mathematical models in which these distributions appear.K_U31, K_U33, K_W02, K_W05 Student is able to determine the basic parameters of the distribution of the random variable.K_U31, K_U33, K_W05 Student is able to build a probabilistic model for a given random event and choose method to calculate probability.K_U30, K_U31, K_U32, K_U33 Student is able to apply basic schemes of probability, including the formula for the total probability and the Bayes' formula.K_U30, K_U31, K_U32, K_U33, K_W05 Student is able to describe discrete random phenomena in the surrounding world using probabilistic language and concepts.K_W03, K_U30, K_W12 Student knows the limitations of his knowledge and understands the need of further learning in field of probability.K_K01 |
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| Assessment methods and assessment criteria: |
The overall form of credit for the course: final exam |
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Classes in period "Academic year 2018/2019" (future)
| Time span: | 2018-10-01 - 2019-06-30 |
 
 see course schedule |
| Type of class: |
Class, 30 hours more information Lecture, 30 hours more information |
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| Coordinators: | Jarosław Kotowicz | |
| Group instructors: | (unknown) | |
| Students list: | (inaccessible to you) | |
| Examination: | Examination |
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