Course detail

Statistical Methods and Risk Analysis

FP-smarPAcad. year: 2017/2018

The course deals with basic ideas and methods of mathematical statistics, methods of regression analysis for description of a trend in time series, and characteristics of time series describing economic and social events.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Learning outcomes of the course unit

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.

Prerequisites

Fundamentals of probability theory.

Co-requisites

Not applicable.

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 theoretical questions,
- submitting answers to elaboration calculating projects.

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 to calculating projects elaboration,
- points achieved by solving examples,
- points achieved by answering theoretical questions.

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

Course curriculum

UNIVARIATE SAMPLE DATA: Univariate sample data with quantitative variable, empirical characteristics and distribution laws, sample data with qualitative variable, point and interval estimation parameters of population, testing statistical hypothesis, goodness-of-fit tests.
BIVARIATE SAMPLE DATA: Bivariate sample data with two quantitative variables, empirical characteristics, interval estimation for correlation coefficient, test of independence two quantitative variables, bivariate sample data with qualitative variables, test of independence two qualitative variables.
REGRESSION ANALYSIS: Least-squares method, regression line, general regression model, special regression function.
TIME SERIES: Characteristics of time series, decomposition of time series, finding of trend in a time series, gliding mean method, season component in a time series.

Work placements

Not applicable.

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.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

KROPÁČ, J. Statistika B. 3. vyd. CERM, Brno: FP VUT, 2012. ISBN 978-80-7204-822-9. (CS)
SEGER, J. aj. Statistické metody v tržním hospodářství. 1. vyd. Praha: Victoria Publishing, 1995. ISBN 80-7187-058.7. (CS)

Recommended reading

WONNACOT, T.H. aj. Statistika pro obchod a hospodářství. 1. vyd. Praha: Victoria Publishing, 1995. ISBN 80-85605-09-0. (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)

Classification of course in study plans

  • Programme BAK Bachelor's

    branch BAK-EP , 2. year of study, summer semester, compulsory

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Syllabus

Topics of lectures are the following:
- Methods of descriptive statistics of a univaried data.
- Parameter and interval estimations.
- Tests of statistical hypothesis.
- The methods of descriptive statistics of a bivaried data.
- Models of regresssion analysis.
- Time series and their characteristics.

The topics of exercise correspond to the topics delt with the lectures.



Exercise

26 hours, compulsory

Teacher / Lecturer