Course detail
Applied Statistics
FP-EasPAcad. year: 2022/2023
The course deals with main ideas and methods of mathematical statistics, methods of regression analysis for description of a trend in time series and characteristics of time series describing economics and social events.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Exercise promote the practical knowledge of the subject presented in the lectures.
Assesment methods and criteria linked to learning outcomes
- points achieved by answering theoretical questions,
- points achieved by computer-aided calculation of projects.
Student obtains the assessment after having a short talk with the tutor where his/her work is evaluated.
The grades and corresponding points:
A (100-91), B (90-81), C (80-71), D (70-61), E (60-50), F (49-0).
Course curriculum
Topics lectures are as follows:
1. Basic concepts of statistical testing.
2. Parametric statistical tests – t-test.
3. Parametric statistical tests – two sample t-test and F-test.
4. Kolmogorov-Smirnov test, Pearson test and Shapiro-Wilk test.
5. Analysis of variance (ANOVA).
6. Nonparametric statistical tests – Sign test, Wilcoxon rank sum test.
7. Nonparametric statistical tests –Kruskal-Wallis test, Friedman test, Spearman's correlation coefficient.
8. Categorical analysis – contingency table and Chi square test.
9. Univariate regression model.
10. Multivariate regression models.
11. The release of the classical assumptions – heteroscedasticity, multicollinearity and autocorrelation of random components.
12. Nonlinear regression models – linearizable regression model and S-curve.
13. Panel data аnalysis.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
- compulsory prerequisite
Statistics 1
Basic literature
KOOP, G. Introduction to econometrics. Chichester : John Wiley & Sons, 2008. 371s. ISBN 978047003270
MATHEWS, P. Design of Experiment with Minitab. Milwaukee: ASQ Quality Press, 2005. ISBN 9780873896375
Recommended reading
Classification of course in study plans
- Programme MGR-EBF Master's 1 year of study, winter semester, compulsory
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
- 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.
- Characteristics of time series.
- Smoothing of time series.
- Panel data.
Exercise
Teacher / Lecturer
Syllabus