Statistics (in English)
- Credits: 6
- Ending: Examination
- Range: 2P + 2C
- Semester: summer
- Year: 1
- Faculty of Economics and Finance
Teachers
Included in study programs
Teaching results
At the end of the semester, students will have a good overview of basic statistical methods, which are currently widely used in various areas of economic practice, more specifically:
Skills
Students will be able to evaluate and identify appropriate statistical methods to achieve the goal of analysis, indicating the possibilities of their further use.
Knowledge
Students will know the principles of basic statistical methods, starting points and conditions of their use. In the final exam, students will use this knowledge to solve tasks in the practical section.
Competencies
Students will know how to:
- apply basic statistical methods,
- correctly interpret and present the obtained results of the analysis,
- evaluate the acquired knowledge and use it further in decision-making in various areas of economic practice.
Indicative content
The course provides an overview of basic statistical methods with a focus on their economic applications.
Support literature
1. Bruce A. Craig, George P. Mccabe, David S. Moore - Introduction to the Practice of Statistics, 2017, W.H.Freeman & Co Ltd, ISBN: 1319153976
2. Joseph C. Watkins - An Introduction to the Science of Statistics: From Theory to Implementation, Preliminary Edition, 2016
3. Andrew Bruce, Peter Gedeck - Practical Statistics for Data Scientists, 2020, USA: O'Reilly Media, Inc, ISBN: 149207294X
Syllabus
1. Stages of statistical research and presentation of statistical data. 2. Characteristics of descriptive statistics - central tendency and variability. 3. Characteristics of descriptive statistics - skewness and kurtosis. Box plot. 4. Principles of random sampling and statistical inference. 5. Point and interval estimates of parameters of one population. 6. Testing statistical hypotheses of one population. 7. Regression and correlation analysis. 8. Analysis of categorical data. 9. Descriptive analysis of time series. 10. Analytical and mechanical smoothing trend in time series. 11. Seasonal decomposition of time series. 12. Individual and aggregate indices and differences.
Requirements to complete the course
Full-time study:
30% preliminary tests (Two mid-term tests, each contributing 15% to the final grade.)
70% written exam (The exam consists of two parts: theoretical - test and open questions, practical - solving examples. The theoretical part contributes 30% and the practical part contributes 40% to the overall assessment.)
Student workload
Total study load (in hours): 156 h
Full time study: participation in lectures 26 hrs, participation in seminars 26 hrs, preparation for seminars 26 hrs, preparation for credit papers 26 hrs, preparation for the exam 52 hrs
Language whose command is required to complete the course
English
Date of approval: 07.02.2022
Date of the latest change: 02.02.2022