Mathematical Statistics 360-MF2-2SM

Course profile: academic
Form of study: stationary
Course type: obligatory
Field of science: natural sciences, disciplines: mathematics, computer and information sciences
Year: 2, semester: 3
Prerequisities: Probabilistic
lecture 30 h. exercise class 20 h, laboratory 10 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 indicators:
- student workload related to classes requiring direct participation of the teacher: 75h, 3 ECTS
- student workload that does not require the teacher's direct participation: 57h, 2 ECTS

Type of course

Mode

(in Polish) w sali

Prerequisites

Probability

Prerequisites (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.

Course coordinators

Jarosław Kotowicz

Learning outcomes

The student knows:
- the most important theorems in the field of mathematical statistics regarding statistical spaces, statistics, exponential statistical spaces, hypothesis testing and estimation, statistical decisions - KA7_WG10.
- the selected package used for statistical data processing (e.g. R/SPSS) - KA7_WG07.
- the fundamentals of Fisher's information theory - KA7_WG10.

The student is able to:
- perform statistical data processing - KA7_UW12.
- determine statistics and estimators with given properties, and the student is also able to test hypotheses - KA7_UW11, KA7_UW12, KA7_UW14.
- prove fundamental theorems of statistics using tools of mathematical analysis, complex analysis and Furier analysis, etc. - KA7_UW05.

Assessment criteria

The overall form of credit for the course: final exam.

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 360-MF2-2SM in USOSweb