Mathematical Statistics
General data
| Course ID: | 0600-FS2-2SM | Erasmus code / ISCED: |
11.105
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(0542) Statistics
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| Course title: | Mathematical Statistics | Name in Polish: | Statystyka matematyczna |
| Department: | (in Polish) Instytut Matematyki | ||
| Course groups: |
(in Polish) 2 rok 2 stopnia sem. zimowy Matematyka spec. Finansowa (in Polish) 2L stac. II st. studia matematyki - przedmioty specjalnościowe (in Polish) 2L stac. II st. studia matematyki finansowej- przedmioty obowiązkowe |
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| ECTS credit allocation (and other scores): |
5.00  view allocation of credits |
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| Language: | Polish | ||
| Type of course: | (in Polish) obowiązkowe specjalnościowe |
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| Prerequisites: | Probability 0600-FS2-1PRB |
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| Short description: |
Course objectives: By the end of the course the student should have developed the skills to: verify when statistics are sufficient (minimum syfficient); determining the loss function; apply statistical decision theory in testing hypotheses. Also know: the advantages and disadvantages of different classes of estimators; how to termine the estimators in the class; properties of exponential statistical spaces and statistics in these spaces. |
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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: 2, semester: 3 Prerequisities: Stochastic Processes lecture 30 h. exercise class 30 h. Verification methods: lectures, exercises, consultations, studying literature, home works, discussions in groups. ECTS credits: 5 Balance of student workload: attending lectures15x2h = 30h attending exercise classes 15x2h = 30h preparation for classes 7x3h = 21h completing notes after exercises and lectures 7x2h = 14h consultations 12x1h = 12h the final examination: preparation.and take 12h + 3h = 15h control works: repeating the material and preparation 3x4h = 12h Quantitative description Direct interaction with the teacher: 75 h., 3 ECTS Practical exercises: 77 h., 3 ECTS |
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| Bibliography: |
(in Polish) 1. J.R. Barra Matematyczne podstawy statystyki, PWN, Warszawa 1982. 2. J. Bartoszewicz Wykłady ze statystyki matematycznej, PWN, Warszawa 1989. 3. R. Zieliński Siedem wykładów wprowadzających do statystyki matematycznej, PWN, Warszawa 1990. |
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| Learning outcomes: |
Learning outcomes: Students know the major theorems of mathematical statistics related to statistical spaces, statistics, exponential statistical spaces, hypothesis testing, theory of estimations, decision theory.K_W03 Students know how to use R/SPSS software for statistical processing of data.K_W12 Students understand fundamentals of mathematical statistics and statistical processing of data bases.K_U12 Students are able to determine the statistics and estimators with selected properties, as well as to test hypotheses.K_U12 Be able to express in writing and oral statistical content.K_U02 Students know foundations of the theory of Fisher information.K_W11 |
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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" (past)
| Time span: | 2018-10-01 - 2019-06-30 |
 
 see course schedule |
| Type of class: |
Class, 20 hours more information Laboratory, 10 hours more information Lecture, 30 hours more information |
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| Coordinators: | Jarosław Kotowicz | |
| Group instructors: | Tomasz Czyżycki, Jarosław Kotowicz | |
| Students list: | (inaccessible to you) | |
| Examination: |
Course -
Examination
Class - Grading Laboratory - Grading |
Classes in period "Academic year 2019/2020" (past)
| Time span: | 2019-10-01 - 2020-06-30 |
see course schedule |
| Type of class: |
Class, 20 hours more information Laboratory, 10 hours more information Lecture, 30 hours more information |
|
| Coordinators: | Jarosław Kotowicz | |
| Group instructors: | Tomasz Czyżycki, Jarosław Kotowicz | |
| Students list: | (inaccessible to you) | |
| Examination: |
Course -
Examination
Class - Grading Laboratory - Grading |
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