| Course title | Probability Theory |
|---|---|
| Course code | KMA/PGSA2 |
| Organizational form of instruction | Lecture |
| Level of course | Doctoral |
| Year of study | not specified |
| Semester | Winter and summer |
| Number of ECTS credits | 5 |
| Language of instruction | Czech, English |
| Status of course | Compulsory-optional |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
|---|
|
| Course content |
|
1. Probability and random variable 2. Random vector 3. Distributions of random variables and vectors 4. Convergence of random variables 5. Measure and probability
|
| Learning activities and teaching methods |
Work with Text (with Book, Textbook)
|
| Learning outcomes |
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To learn basics of probability theory.
Comprehension Understanding of basics of probability theory. |
| Prerequisites |
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Mathematical analysis and linear algebra on master level in Applied Mathematics.
|
| Assessment methods and criteria |
|
Oral exam
Oral exam: to know and to understand the subject. |
| Recommended literature |
|
| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
|---|---|---|---|---|
| Faculty: Faculty of Science | Study plan (Version): Applied Mathematics (2020) | Category: Mathematics courses | - | Recommended year of study:-, Recommended semester: - |
| Faculty: Faculty of Science | Study plan (Version): Applied Mathematics (2025) | Category: Mathematics courses | - | Recommended year of study:-, Recommended semester: - |