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(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.
Course descriptions are protected by copyright.
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