University of Bialystok - Central Authentication SystemYou are not logged in | log in
course directory - help

Mathematical Statistics

General data

Course ID: 0600-FS2-2SM Erasmus code / ISCED: 11.105 / (0542) Statistics
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
ECTS credit allocation (and other scores): 5.00
view allocation of credits
Language: Polish
Type of course:

(in Polish) obowiązkowe specjalnościowe
obligatory courses

Prerequisites:

Probability 0600-FS2-1PRB

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.

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

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.

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

Assessment methods and assessment criteria:

The overall form of credit for the course: final exam

Classes in period "Academic year 2018/2019" (past)

Time span: 2018-10-01 - 2019-06-30
Choosen plan division:


magnify
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

Classes in period "Academic year 2019/2020" (in progress)

Time span: 2019-10-01 - 2020-06-30
Choosen plan division:


magnify
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
Course descriptions are protected by copyright.
Copyright by University of Bialystok.