Course detail

Statistics 2

FP-stat2PAcad. year: 2023/2024

The course deals with main ideas and methods of point and interval estimates, the most used parametric and nonparametric tests, good fit tests, an analysis of variance, a categorial analysis, linear and nonlinear multiple regression models and time series analysis.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. RNDr. Bedřich Půža, CSc.

Department

Institute of Informatics (ÚI)

Entry knowledge

Fundamentals of a probability theory and a random variable.

Rules for evaluation and completion of the course

The course-unit credit is awarded on the following conditions (max. 40 points):
- submitting answers to calculating problems and theoretical questions.

The exam (max. 60 points)
- has a written form.
In the first part of the exam student solves 4 examples within 80 minutes. 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 questions and theoretical questions,
- points achieved by solving examples,
- points achieved by answering theoretical questions.

The grades and corresponding points:
A (100-90), B (89-80), C (79-70), D (69-60), E (59-50), F (49-0).
Attendance at lectures is not compulsory but is recommended.

Aims

The objective of this course is to familiar students with ideas and methods of point and interval estimates, the most used parametric and nonparametric tests, good fit tests, an analysis of variance, a categorial analysis, linear and nonlinear multiple regression models and time series analysis.
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 economics problems. After completion of this course students will be prepared to use these methods in economics courses.

Study aids

see Course literature.
Study materials available on e-learning.

Prerequisites and corequisites

Not applicable.

Basic literature

BUDÍKOVÁ, M.; LERCH, T. a MIKOLÁŠ, Š. Základní statistické metody. Brno: Masarykova univerzita v Brně, 2005. ISBN 80-210-3886-1. hospodářství. Praha : Victoria Publishing, 1995. ISBN 80-7187-058-7.
Studijní materiály dostupné na e-learningu. (CS)

Recommended reading

ARLT, J. a ARLTOVÁ, M. Ekonomické časové řady. Praha: Professional Publishing, 2009. ISBN 978-808-6946-85
GUJARATI, D. N. a  PORTER, D.C. Basic econometrics. 5th ed. Boston: McGraw-Hill Irwin, 2009. ISBN 978-007-3375-779.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme MGR-MEO Master's 1 year of study, winter semester, compulsory
  • Programme MGR-UFRP Master's 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Karel Doubravský, Ph.D.

Syllabus

Topics of lectures are the following:
- Data samples.
- Parameter and interval estimations.
- Testing statistical hypothesis (Parametric and Nonparametric tests).
- Analysis of variance (ANOVA).
- Caterogical analysis.
- Univariate regression models.
- Multivariate regression models.
- Nonlinear regression models.

-Logistic regression.
- Time series analysis
- Panel data.

Exercise

13 hod., compulsory

Teacher / Lecturer

Ing. Karel Doubravský, Ph.D.

Syllabus

Exercise promote the practical knowledge of the subject presented in the lectures.

Elearning

eLearning: currently opened course