Course title | Mathematical Statistics |
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Course code | KMA/PGSA3 |
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) |
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Course content |
1. Elementary statistical inference 2. Maximum likelihood method 3. Sufficient statistics 4. Hypotheses testing 5. Inference under the normality assumption 6. Nonnaprametric statistics 7. Bayesian statistics 8. Linear models
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Learning activities and teaching methods |
Work with Text (with Book, Textbook)
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Learning outcomes |
To get an overview about methods of mathematical statistics.
Comprehension Understanding of basic methods of mathematical statistics. |
Prerequisites |
Basic course in probability theory (doctoral level).
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Assessment methods and criteria |
Oral exam
Oral exam: to know and to understand the subject. |
Recommended literature |
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Study plans that include the course |
Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
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Faculty: Faculty of Science | Study plan (Version): Applied Mathematics (2020) | Category: Mathematics courses | - | Recommended year of study:-, Recommended semester: - |