Course detail

# Statistics 2

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

5

Mode of study

Not applicable.

Vstupní znalosti

Fundamentals of a probability theory and a random variable.

Pravidla hodnocení a ukončení předmětu

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.

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.

Učební cíle

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.

Studijní opory

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

Prerequisites and corequisites

Not applicable.

Basic literature

Studijní materiály dostupné na e-learningu.

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

GUJARATI, D. N. a D. C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill Irwin, 2009. ISBN 978-007-3375-779.Svoboda, 1977.
ARLT, J. a M. ARLTOVÁ. Ekonomické časové řady. Praha: Professional Publishing, 2009. ISBN 978-808-6946-85

eLearning

Classification of course in study plans

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

#### Type of course unit

Lecture

26 hours, optionally

Teacher / Lecturer

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 hours, compulsory

Teacher / Lecturer

Syllabus

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

eLearning