Economic statistics

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Institute of Economic Studies

Synopsis:

In the subject of Economic statistics will be the students understood the interpretation of basic statistical methods, which bought off when processing, presentation, and analysis of economic and social phenomena. The choice of the specific methods and their clarification is subordinate to the interest in highlighting the processes and applications that are typical for the analytical and decision-making activities not only of economists and of managers.

Requirements:

SW: MS Excel, Gretl

Syllabus of lectures:

1. The repetition of the subject of statistics 1. Descriptive statistics-characteristics of location, variability. The basic distribution of probabilities - discrete, continuous. Hypothesis testing-a basic parametric and non-parametric tests, conformance tests, the test for independence, tests for verification of normal distribution, Kolmogorov-Smirnov-probability test, Shapiro-Wilk's test, etc.

2. Multivariate Statistics I. Analysis of Variance (Anova). Validating input assumptions for Anova. One factor Anova, two factor Anova, the triple classification. Tests of conformity of variances-Bartllett test, Cochran's test, Hartley test.

3. Multivariate Statistics II. Multiple comparisons for the analysis of variance. Tukeyuv test Scheffé´s method, Duncan's multiple range test. Non-parametric multivariate statistics. Kruskal-Wallis test, Friedman test. Multiple comparison with nonparametric matching tests.

4. Correlation analysis. Hypothesis testing about correlation coefficient. Confidence interval for correlation coefficient. The selection coefficient of partial correlation and multiple correlation. Tetrachoric correlation coefficient, the coefficient of biserial correlation.

5. Regression analysis I. The simple linear regression model, other types of linear regression models. Variability for simple linear regression. Confidence intervals for the parameters.

6. Regression analysis II. Evaluation of the quality of the simple linear regression model. Testing hypotheses about the values of the parameters of the regression line and functional values. Non-linear models, which can transformed to a linear shape.

7. The multidimensional model of linear regression. Verification of the provided multicollinearity. Evaluation of the quality of a multidimensional linear regression model.

8. Violation of the fundamental assumptions of the linear regression model. Residual analysis. Tests for homoscedasticity. Autocorrelation.

9. Introduction to multivariate statistical methods. An overview of the methods. - The principle of the use of cluster analysis, clustering methods.

10. Introduction to time series. Description of the time series. Basic concepts.

11. Time series I. Basic characteristics of the time series. Dynamic characteristics of the time series. Decomposition of time series.

12. Time series (II). Basic characteristics of the time series. Dynamic characteristics of the time series. Decomposition of time series.

13. Time series III. The search trend. An overview of the current trend of curves. Choosing the right model of the trend.

14. Time series IV. Moving averages. Time series smoothing.

Syllabus of tutorials:

Study Objective:

Objective of the course in terms of learning outcomes and competences The aim of the course is to acquaint students with basic methods in evaluation of one-dimensional and two-dimensional sample statistical files, to acquaint with methods of dependency analysis, modeling and analysis of time series and basic types of indexes used for comparison of economic indicators. Students will learn about the use of statistical methods in economic practice and will learn how to compute and interpret the achieved results.

Includes the interpretation of time series.

Study materials:

BUDÍKOVÁ, M., KRÁLOVÁ, M., MAROŠ, B. Průvodce statistickými metodami. Praha: Grada Publishing, 2010. ISBN 978-80-247-3243-5.

HEBÁK, P., HUSTOPECKÝ, J. Vícerozměrné statistické metody 1. Praha: Informatorium. 2006. ISBN 978-80-7333-056-9.

HEBÁK, P., HUSTOPECKÝ, J., MALÁ, I. Vícerozměrné statistické metody 2. Praha: Informatorium. 2005. ISBN 978-80-7333-036-9.

Hindls, R. a kol. Statistika pro ekonomy. Praha: Profesional Publishing. 2007.ISBN 8086946436

Note:

Further information:

http://moodle-vyuka.cvut.cz/

No time-table has been prepared for this course

The course is a part of the following study plans:

• N-PRI-prez.forma od 15/16 (compulsory course)
• N-PRI-prez.forma od 16/17 (compulsory course)
• N-PRI-prez.forma od 17/18 (compulsory course)