Statistical Methods 2600-ABdz1MSZUf
1. Graphical presentation of data
2. Measures of tendency, dispersion, variability
3. Comparing data sets
4. Testing parametric hypotheses
5. Testing non-parametric hypotheses
6. Statistical inference - related to diploma theses
Type of course
Course coordinators
Learning outcomes
Upon completion of the course, the student:
In terms of knowledge:
K_W01 - knows and understands at the basic level research methodology and terminology in the field of discipline of management and quality science and in supplementary disciplines (economics and finance, legal sciences), in particular the use of quantitative analysis tools.
K_W03 - knows and understands in a deepened manner theories and economic models (in particular constructed by analytical methods) regarding the functioning of a business organization.
In terms of skills:
K_U02 - can correctly interpret technological, social, political, legal, economic, ecological and their impact on the functioning of the organization and the entire economy, using the right selection of calculation methods.
In terms of competences:
K_K01 - is ready to assess and critically approach the situation and phenomena related to the functioning of the organization, sector and the entire economy using quantitative models.
Assessment criteria
During the semester, students are obliged to write one test consisting of open computational tasks; At least 60% of the points are required to pass.
Learning outcomes will be verified on an ongoing basis using the tasks performed by participants during classes and by assessing the results of the colloquium
Obtaining 60% of the maximum number of points from the test.
Practical placement
Internship is not required to complete the course.
Bibliography
Sobczyk M., Statystyka, PWN, Warszawa 2010 i dalsze wydania
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: