| Course title | Mathematical Statistics | 
|---|---|
| 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 | 
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        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 | 
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                To get an overview about methods of mathematical statistics.
                 Comprehension Understanding of basic methods of mathematical statistics.  | 
        
| Prerequisites | 
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                Basic course in probability theory (doctoral level).
                
                
                    
                        
                    
                    
                
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| Assessment methods and criteria | 
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                        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 | |
|---|---|---|---|---|
| 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: - |