(in Polish) Statystyka matematyczna-przedmiot oferowany w języku angielskim

General data

Course ID:	0300-MS2-1STM#E
Erasmus code / ISCED:	(unknown) / (unknown)
Course title:	(unknown)
Name in Polish:	Statystyka matematyczna-przedmiot oferowany w języku angielskim
Organizational unit:	(in Polish) Zakład Polityki Regionalnej i Zarządzania Projektami
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:	English
Type of course:	(in Polish) podstawowe obligatory courses
Requirements:	Descriptive Statistics 0300-MS1-1STA#E Mathematics 0300-MS1-1MAT#E
Prerequisites:	Descriptive Statistics 0300-MS1-1STA#E Mathematics 0300-MS1-1MAT#E
Prerequisites (description):	(in Polish) Mathematics in the field of: differential and integral calculus of functions of one variable; linear algebra Probability theory: secondary school level; Descriptive statistics in the field of: structure analysis (average measures, variability, asymmetry), analysis of relationships between variables.
Mode:	(in Polish) w sali
Short description:	(in Polish) Developing knowledge and skills in the field of designing and conducting statistical surveys in accordance with statistical inference standards. After completing the course, students should have a basic knowledge of statistical inference methods and the ability to apply these methods in practice. Elements of probability theory: discrete and continuous variables, probability distributions, joint, boundary and conditional distributions. Simple random sample, elements of point and interval estimation theory and hypothesis verification.
Full description:	(in Polish) Educational profile: general academic Form of study: stationary Course type: obligatory, primary course Field and discipline of science: field: mathematical sciences; discipline: mathematics Year/semester: 1 year/1 semester Prerequisites: 0300-MS1-1MAT#E Mathematics, 0300-MS1-1STA#E Economic Statistics Number of didactic hours: 15 hours - lecture, 30 hours - classes Teaching methods: Traditional lecture conducted with the use of multimedia presentations, practical and activating methods (individual work, group work) The general form of passing the course: passing classes + exam ESTS points: 6 Student workload balance: participation in lectures - 15 hours participation in classes - 30 hours participation in consultations hours - 4 hours doing homework - 10 hours preparation for classes - 36 hours preparation for the test - 25 hours preparation for the exam and participation in the exam - 30 hours The total student workload - 150 hours Quantitative indicators Student workload related to the course: Number of hours / ECTS points requiring direct teacher participation: 50/2 of a practical nature: 105/4,2
Bibliography:	(in Polish) Ostasiewicz K. A., Mathematical statistics, Publishing House of Wrocław University of Economics, Wrocław 2014. Michna Z., Statistics, Publishing House of Wrocław University of Economics, Wroclaw 2014.
Learning outcomes:	(in Polish) KNOWLEDGE 1STM_W01: Knows the concept, properties, basic parameters and selected distributions of random varaible. M2_W06 1STM_W02: Knows the distribution of basic statistics from the sample, point and interval estimation methods, and selected significance tests. M2_W06 SKILLS 1STM_U01: Is able to design and conduct statistical research in accordance with statistical inference standards. M2_U04 1STM_U02: Is able to interpret results and infer about the population based on results from a random sample. M2_U04 SOCIAL COMPETENCE 1STM_K01: Is able to individually expand knowledge and skills in mathematical statistics. M2_K06
Assessment methods and assessment criteria:	(in Polish) The condition of passing the course is to achieve assumed learning outcomes. Assessment methods of lectures: written or oral exam. Students who have completed the classes are allowed to take the exam. Assessment methods of classes: test and activity during the classes. Leaving the student more than 4 hours qualify to fail the subject. Completing the absences takes place during the teacher's consultation hours.

This course is not currently offered.

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