Mathematical Statistics
General data
Course ID:  0600FS22SM#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 

Requirements:  Probability 0600FS21PRB#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" (future)
Time span:  20181001  20190630 
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 
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