Mathematical Statistics

General data

Course ID:	0600-FS2-2SM
Erasmus code / ISCED:	11.105 The subject classification code consists of three to five digits, where the first three represent the classification of the discipline according to the Discipline code list applicable to the Socrates/Erasmus program, the fourth (usually 0) - possible further specification of discipline information, the fifth - the degree of subject determined based on the year of study for which the subject is intended. / (0542) Statistics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Mathematical Statistics
Name in Polish:	Statystyka matematyczna
Organizational unit:	(in Polish) Instytut Matematyki.
Course groups:
ECTS credit allocation (and other scores):	(not available) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. 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

This course is not currently offered.

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