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Mathematical Statistics

Informacje ogólne

Kod przedmiotu: 330-ERA-2MS Kod Erasmus / ISCED: 14.3 / (0311) Ekonomia
Nazwa przedmiotu: Mathematical Statistics
Jednostka: Wydział Ekonomii i Finansów
Grupy: WEiF zima Erasmus
Punkty ECTS i inne: 6.00
Język prowadzenia: angielski
Rodzaj przedmiotu:

obowiązkowe
podstawowe

Założenia (lista przedmiotów):

Matematyka - przedmiot oferowany w języku angielskim 330-MS1-1MAT#E
Statystyka opisowa-przedmiot oferowany w języku angielskim 330-MS1-1STA#E

Założenia (opisowo):

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.

Tryb prowadzenia przedmiotu:

mieszany: w sali i zdalnie

Skrócony opis:

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.

Pełny opis:

Educational profile: general academic

Form of study: stationary

Course type: obligatory, M_2 primary courses

Year/semester: 1 year/2 semester

Prerequisites : knowledge of mathematics and descriptive statistics at the level of a first-cycle graduate

Number of didactic hours: 15 hours - lecture, 30 hours - classes

Teaching methods:

Lectures conducted with the use of multimedia presentations and engaging students to actively participate in discussions during the lecture.

Classes - excersises solving, statistical analysis, group discussion

ESTS points: 6

Student workload balance:

participation in lectures - 15 hours

participation in classes - 30 hours

participation in consultations hours - 9 hours

preparation for classes - 60 hours

preparation for lectures - 20 hours

preparation for the test and exam - 20 hours

participation in the exam - 1 hour

Quantitative indicators

Student workload related to the course:

Number of hours / ECTS points

requiring direct teacher participation: 46/1,84

of a practical nature: 50/2

Literatura:

Ostasiewicz K. A., Mathematical statistics, Wrocław University of Economics Publishing House, Wrocław 2014.

Kowalczyk B., Witkowski B., Mathematical statistics for management, Warsaw School of Economics Publishing House, Warsaw 2015.

Michna Z., Statistics, Wrocław University of Economics Publishing House, Wroclaw 2014.

Efekty uczenia się:

NOWLEDGE

1STM_W01: Knows the concept, properties, basic parameters and selected distributions of random varaible. KP7_WG5

1STM_W02: Knows the distribution of basic statistics from the sample, point and interval estimation methods, and selected significance tests. KP7_WG5

SKILLS

1STM_U01: Is able to design and conduct statistical research in accordance with statistical inference standards. KP7_UK4

1STM_U02: Is able to interpret results and infer about the population based on results from a random sample. KP7_UK4

SOCIAL COMPETENCE

1STM_K01: Is able to individually expand knowledge and skills in mathematical statistics. KP7_KK2

Metody i kryteria oceniania:

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.

Zajęcia w cyklu "Rok akademicki 2020/21" (w trakcie)

Okres: 2020-10-01 - 2021-06-30
Wybrany podział planu:


powiększ
zobacz plan zajęć
Typ zajęć: Ćwiczenia, 30 godzin więcej informacji
Wykład, 15 godzin więcej informacji
Koordynatorzy: Zofia Karczewska, Iwona Skrodzka
Prowadzący grup: Iwona Skrodzka
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Egzamin
Ćwiczenia - Zaliczenie na ocenę
Rodzaj przedmiotu:

nieobowiązkowe

Tryb prowadzenia przedmiotu:

zdalnie

Skrócony opis:

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.

Pełny opis:

Educational profile: general academic

Form of study: stationary

Course type: obligatory, M_2 primary courses

Year/semester: 1 year/2 semester

Prerequisites : knowledge of mathematics and descriptive statistics at the level of a first-cycle graduate

Number of didactic hours: 15 hours - lecture, 30 hours - classes

Teaching methods:

Lectures conducted with the use of multimedia presentations and engaging students to actively participate in discussions during the lecture.

Classes - excersises solving, statistical analysis, group discussion

ESTS points: 6

Student workload balance:

participation in lectures - 15 hours

participation in classes - 30 hours

participation in consultations hours - 9 hours

preparation for classes - 60 hours

preparation for lectures - 20 hours

preparation for the test and exam - 20 hours

participation in the exam - 1 hour

Quantitative indicators

Student workload related to the course:

Number of hours / ECTS points

requiring direct teacher participation: 46/1,84

of a practical nature: 50/2

Literatura:

Ostasiewicz K. A., Mathematical statistics, Wrocław University of Economics Publishing House, Wrocław 2014.

Kowalczyk B., Witkowski B., Mathematical statistics for management, Warsaw School of Economics Publishing House, Warsaw 2015.

Michna Z., Statistics, Wrocław University of Economics Publishing House, Wroclaw 2014.

Uwagi:

In the 2020/2021 education cycle, due to the limitations resulting from the COVID-19 pandemic, classes are held remotely using the MS Teams platform.

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