Course detail
Statistical Methods and Risk Analysis
FP-smarPAcad. year: 2021/2022
The course deals with basic ideas and methods of mathematical statistic: methods of analysis of multidimensional data files, methods of regression and correlation analysis, methods of regression analysis for description of a trend in time series, and characteristics of time series describing economic and social events, index analysis.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
(theory of probability: random events, classical probability, conditional probability;
discret and continuous random variables: distribution function, density, Binomical and Poisson distribution, normal distribution;
estimation of confidence interval , hypothesis testing)
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
CREDIT: Credit is awarded on the basis of:
- points for tests
- tests cannot be repeated
EXAM: The exam is written, it consists of theory (time about 20 minutes)
The grades, corresponding to the sum (max. 100 points), consists of:
- points for tests (30 + 30 + 25 for 3 tests)
- points for the exam (15 points)
- there is a requirement for a minimum score for the test
Marks and corresponding points:
A (100-90), B (89-80), C (79-70), D (69-60), E (59-50), F (49-0)
In the case of distance learning:
- credit and exam will be solved on the basis of how long the full-time form of teaching will be maintained
- the effort will be that it is possible to carry out credit tests in person at the faculty (even if the teaching takes place online), even within one day at the end of the semester
- if the exam and credit tests had to be distance, then probably 1 comprehensive credit test would take place and then an oral exam via Microsoft Teams
Course curriculum
week 1: Discrete and continuous random variables, distribution function, density, special types of probability distrubiutions
week 2: Construction of confidence intervals; hypothesis testing
week 3: Methods of measuring the relationship between quantitative variables: covariance coefficient, correlation coefficient
week 4: Methods of measuring the relationship between quantitative variables: test of independence
week 5: Methods of measuring the relationship between qualitative variables: test of independence
week 6: 2x2 tables, NcNemar's test
week 7: Regression and correlation analysis. Regression line.
week 8: Regression analysis: another types of regression functions.
week 9: Times series - introduction. Characteristics of time series. Decomposition of time series.
week 10: Time series - estimation of trend in time series. Seasonal and cyclical component.
week 11: Index analysis - simple and complex individual indexes, agregate indexes.
week 12: Decision-making under risk.
week 13: Decision trees.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
SEGER, J. aj. Statistické metody v tržním hospodářství. 1. vyd. Praha: Victoria Publishing, 1995. ISBN 80-7187-058.7. (CS)
Recommended reading
KROPÁČ, J. Statistika. 5. vyd. CERM, Brno: 2013. ISBN 978-80-7204-835-9. (CS)
WONNACOT, T.H. aj. Statistika pro obchod a hospodářství. 1. vyd. Praha: Victoria Publishing, 1995. ISBN 80-85605-09-0. (CS)
Classification of course in study plans