(in Polish) Statystyka WM-MA-S1-E6-STA
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.
(in Polish) Dyscyplina naukowa, do której odnoszą się efekty uczenia się
(in Polish) E-Learning
(in Polish) Grupa przedmiotów ogólnouczenianych
(in Polish) Opis nakładu pracy studenta w ECTS
Subject level
Learning outcome code/codes
Type of subject
Preliminary Requirements
Course coordinators
Learning outcomes
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 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
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: