Course detail

Statistical Methods and Risk Analysis

FP-smarPAcad. year: 2018/2019

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.

Learning outcomes of the course unit

Students will be made familiar with the methods of mathematical statistics, methods of analysis of multidimensional data files, methods of regression and correlation analysis, methods of analysis of time series analysis and methods of index analysis and will learn how to use the respective methods when solving economic problems. After completion of this course students will be prepared to use these methods in economic courses.

Prerequisites

Fundamentals of probability theory and fundamentals of mathematical statistics (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

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

KROPÁČ, J. Statistika B. 3. vyd. CERM, Brno: FP VUT, 2012. ISBN 978-80-7204-822-9. (CS)
WONNACOT, T.H. aj. Statistika pro obchod a hospodářství. 1. vyd. Praha: Victoria Publishing, 1995. ISBN 80-85605-09-0. (CS)
SEGER, J. aj. Statistické metody v tržním hospodářství. 1. vyd. Praha: Victoria Publishing, 1995. ISBN 80-7187-058.7. (CS)
KROPÁČ, J. Statistika. 5. vyd. CERM, Brno: 2013. ISBN 978-80-7204-835-9. (CS)
HINDLS, R. aj. Analýza dat v manažerském rozhodování. Praha: Grada Publishing, 1999. ISBN 80-7169-255-7. (CS)

Planned learning activities and teaching methods

The course contains lectures that explain basic principles, problems and methodology of the discipline, and exercises that promote the practical knowledge of the subject presented in the lectures.

Assesment methods and criteria linked to learning outcomes

COURSE-UNIT CREDIT: The course-unit credit is awarded on the following conditions:
- participation in seminars,
- submitting answers to excercises.

EXAM: The exam has a written form.
In the first part of the exam student solves 4 examples within 80 minutes. (It is allowed to use recomended literature.)
In the second part of the exam student works out answers to 3 theoretical questions within 15 minutes.
The mark, which corresponds to the total sum of points achieved (max 100 points), consists of:
- points achieved in control tests,
- points achieved by solving examples,

The grades and corresponding points:
A (100-90), B (89-83), C (82-76), D (75-69), E (68-60), F (59-0).

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

Students will be made familiar with the methods of mathematical statistics, regression analysis and time series analysis and will learn how to use the respective methods when solving economic problems. After completion of this course students will be prepared to use these methods in economic courses.

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.

Aims

The objective of the course is to make students familiar with the fundamental ideas and methods used by these mathematical disciplines which enable students to apply this knowledge when solving problems related to the economic areas where these methods are used.

Specification of controlled education, way of implementation and compensation for absences

Attendance at lectures is not compulsory but is recommended. Attendance at exercises is required and checked by the tutor. An excused absence of a student from seminars can be compensated for by submitting solution of alternate exercises.

Classification of course in study plans

  • Programme BAK-EP Bachelor's, 3. year of study, winter semester, 5 credits, compulsory-optional

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Exercise

13 hours, compulsory

Teacher / Lecturer