Statistics
General data
Course ID: | WM-MA-Z-STA |
Erasmus code / ISCED: |
(unknown)
/
(0541) Mathematics
|
Course title: | Statistics |
Name in Polish: | Statystyka |
Organizational unit: | Faculty of Mathematics and Natural Sciences. School of Exact Sciences. |
Course groups: | |
ECTS credit allocation (and other scores): |
8.00
|
Language: | Polish |
(in Polish) Dyscyplina naukowa, do której odnoszą się efekty uczenia się: | mathematics |
Subject level: | elementary |
Learning outcome code/codes: | MA1_W01, MA1_W03,MA1_W04, MA1_W05,MA1_W08; MA1_U09, MA1_U11,MA1_U30, MA1_U31,MA1_U32, MA1_U33,MA1_U34, MA1_U35,MA1_U36; MA1_K02; |
Preliminary Requirements: | Knowledge of: mathematical analysis I, algebra with geometry I, probability theory I. |
Full description: |
The aim of the course is to provide knowledge of the basics of mathematical statistics and statistical inference. In lecture, students master the knowledge of the assumptions and construction of statistical models and their role in statistical inference. In exercises and laboratory, students master methods of practical application of statistical models in other fields. |
Efekty kształcenia i opis ECTS: |
In the field of lecture, the student: W1. has knowledge of the place of statistics in mathematics and its applications (MA1_W01); W2. has knowledge of the construction and analysis of simple mathematical-statistical models based on basic mathematical theories and their applications in other sciences (MA1_W03); W3. knows basic theorems of descriptive and mathematical statistics (MA1_W04); W4. knows examples illustrating basic statistical concepts (MA1_W05); W5. knows the basics of computational techniques in the area of descriptive and mathematical statistics (MA1_W08) In the area of exercises and laboratory, the student: U1. is able to assign appropriate functions with their properties to statistical issues (MA1_U09); U2. is able to interpret and apply quantitative and graphical methods of presenting data and their interdependencies (MA1_U11); U3. is able to construct and analyse a mathematical model of a random experiment and uses the concepts of probabilistic and statistical space (MA1_U30); U4. knows practical applications of basic (discrete and continuous) probability distributions (MA1_U31); U5. is able to apply the integral p-value and Bayesian formulas (MA1_U32); U6. is able to estimate the parameters of parametric distributions, also using CLT (MA1_U33); U7. is able to use statistical population characteristics and their sample equivalents (MA1_U34); U8. is able to make simple statistical inferences, also using computer tools (MA1_U35); U9. is able to talk about statistical issues in understandable language (MA1_U36) and K1. is prepared to formulate questions to deepen a broader understanding of the problem being solved (MA1_K02). |
Assessment methods and assessment criteria: |
For all effects, the following assessment criteria are adopted for all forms of verification: grade 5: fully achieved (no obvious shortcomings) grade 4.5: achieved almost fully and criteria for awarding a higher grade are not met grade 4: largely achieved and the criteria for a higher grade are not met grade3.5: largely achieved -with a clear majority of positives -and the criteria for granting a higher grade are not met grade 3: achieved for most of the cases covered by the verification and criteria for a higher grade are not met grade 2: not achieved for most of the cases covered by the verification |
Classes in period "Summer semester 2021/22" (past)
Time span: | 2022-02-01 - 2022-06-30 |
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MO TU W TH FR SA WYK
LAB
CW
|
Type of class: |
Classes, 10 hours
Laboratory, 20 hours
Lectures, 20 hours
|
|
Coordinators: | Oleg Tikhonenko | |
Group instructors: | Piotr Śliwka, Oleg Tikhonenko | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
examination
Classes - graded credit Laboratory - graded credit Lectures - examination |
|
(in Polish) E-Learning: | (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
|
Type of subject: | obligatory |
|
(in Polish) Grupa przedmiotów ogólnouczenianych: | (in Polish) nie dotyczy |
Classes in period "Summer semester 2022/23" (past)
Time span: | 2023-02-01 - 2023-06-30 |
Navigate to timetable
MO TU W TH FR SA LAB
WYK
CW
LAB
SU WYK
CW
|
Type of class: |
Classes, 10 hours
Laboratory, 20 hours
Lectures, 20 hours
|
|
Coordinators: | Piotr Śliwka, Oleg Tikhonenko | |
Group instructors: | Piotr Śliwka, Oleg Tikhonenko | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
examination
Classes - graded credit Laboratory - graded credit Lectures - examination |
|
(in Polish) E-Learning: | (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
|
(in Polish) Opis nakładu pracy studenta w ECTS: | Lecture Estimated student workload participation in classes - 20 h participation in the examination - 2 h consultations with the lecturer - 3 h preparation for classes - 10 h exam preparation - 40 h altogether 75 h, which corresponds to 3 ECTS Exercises Estimated student workload participation in classes - 10 h participation in the assessment - 2 h consultations with the lecturer - 3 h preparation for classes - 10 h preparation for the credit - 25 h total 50 h, which corresponds to 2 ECTS Laboratories participation in classes - 20 h consultations with the tutor - 2 h homework - 33 h preparation for verification - 20 h altogether 75 h, which corresponds to 3 ECTS |
|
Type of subject: | obligatory |
|
(in Polish) Grupa przedmiotów ogólnouczenianych: | (in Polish) nie dotyczy |
Classes in period "Summer semester 2023/24" (in progress)
Time span: | 2024-02-15 - 2024-06-30 |
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MO TU W TH FR SA LAB
LAB
SU WYK2
WYK2
CW3
WYK2
CW3
CW3
|
Type of class: |
Classes, 10 hours
Laboratory, 20 hours
Lectures, 20 hours
|
|
Coordinators: | Oleg Tikhonenko | |
Group instructors: | Piotr Śliwka, Oleg Tikhonenko | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
examination
Classes - graded credit Laboratory - graded credit Lectures - examination |
|
(in Polish) E-Learning: | (in Polish) E-Learning |
|
(in Polish) Opis nakładu pracy studenta w ECTS: | Lecture Estimated student workload participation in classes - 20 h participation in the examination - 2 h consultations with the lecturer - 3 h preparation for classes - 10 h exam preparation - 40 h altogether 75 h, which corresponds to 3 ECTS Exercises Estimated student workload participation in classes - 10 h participation in the assessment - 2 h consultations with the lecturer - 3 h preparation for classes - 10 h preparation for the credit - 25 h total 50 h, which corresponds to 2 ECTS Laboratories participation in classes - 20 h consultations with the tutor - 2 h homework - 33 h preparation for verification - 20 h altogether 75 h, which corresponds to 3 ECTS |
|
Type of subject: | obligatory |
|
(in Polish) Grupa przedmiotów ogólnouczenianych: | (in Polish) nie dotyczy |
Classes in period "Summer semester 2024/25" (future)
Time span: | 2025-02-15 - 2025-06-30 |
Navigate to timetable
MO TU W TH FR |
Type of class: |
Classes, 10 hours
Laboratory, 20 hours
Lectures, 20 hours
|
|
Coordinators: | (unknown) | |
Group instructors: | (unknown) | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
examination
Classes - graded credit Laboratory - graded credit Lectures - examination |
|
(in Polish) E-Learning: | (in Polish) E-Learning |
|
Type of subject: | obligatory |
|
(in Polish) Grupa przedmiotów ogólnouczenianych: | (in Polish) nie dotyczy |
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