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Mathematical Statistics

General data

Course ID: 0600-FS2-2SM#a Erasmus code / ISCED: (unknown) / (unknown)
Course title: Mathematical Statistics Name in Polish: Mathematical Statistics
Department: Faculty of Mathematics and Informatics
Course groups: (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: English
Type of course:

(in Polish) obowiązkowe specjalnościowe
obligatory courses


Probability 0600-FS2-1PRB#a

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 10x2h = 20h

attending laboratory 10x1h = 10h

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

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" (in progress)

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

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: (unknown)
Students list: (inaccessible to you)
Examination: Examination
Course descriptions are protected by copyright.
Copyright by University of Bialystok.