Course detail

Statistics

FP-BstatPAcad. year: 2019/2020

Random Events: Probability and their properties, conditioned probability, classical probability, independed events, total probability.
Random Variables: Random variables of discrete and continuous type, characteristics and distribution laws, distribution binomial, hypergeometric, geometric, Poisson, normal and exponential.
Mathematical Statistics: Processing univariate sample data with a quantitative variable, points and intervals estimation of population parameters, testing statistical hypothesis.
Index Numbers: Simple and composite index numbers, Laspeyres and Paasche index numbers.
Regression Analysis: Method of least-squares, regression line, special regression function.
Time Series: Characteristics of time series, decomposition of time series, trend in a time series.

Learning outcomes of the course unit

Students will be made familiar with the fundamentals of random variables, mathematical statistics, analysis of index numbers, regression analysis and time series and will learn how to use its methods to solve economic problemes. After completion of this course students will be prepared to study economic topics working with uncertainty.

Prerequisites

Fundamentals of linear algebra and mathematical analysis.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

HINDLS, R. aj. Analýza dat v manažerském rozhodování. Praha : Grada Publishing, 1999. ISBN 80-7169-255-7. (CS)
KROPÁČ, J. Statistika. 2. vyd. Brno: CERM, 2012. ISBN 978-80-7204-788-8. (CS)
SWOBODA, H. Moderní statistika. Praha : Svoboda, 1977. (CS)
SEGER, J. aj. Statistické metody v tržním hospodářství. Praha : Victoria Publishing, 1995. ISBN 80-7187-058-7. (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 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, achieved to calculating projects elaboration;
- 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).

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

Random events.
Discrete random variables.
Continuous random variables.
Processing data samples.
Tests of statistical hypotheses.
Composite and aggregate index numbers.
Regression analysis.
Time series.

Aims

The objective of the course is to make students familiar with the fundamentals of random variables, mathematical statistics, analysis of index numbers, regression analysis and time series. They will be able to study economic topics working with uncertainty, and to solve problems related to these topics applying the methods of this theory.

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 Bachelor's

    branch BAK-EPM , 2. year of study, winter semester, 5 credits, compulsory

Type of course unit

 

Lecture

26 hours, compulsory

Teacher / Lecturer

Exercise

26 hours, compulsory

Teacher / Lecturer

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