INMBASTE Statistical Methods for Economists

School of Business Administration in Karvina
Summer 2026
Extent and Intensity
2/1/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Mgr. Jiří Mazurek, Ph.D. (lecturer)
Guaranteed by
doc. Mgr. Jiří Mazurek, Ph.D.
Department of Informatics and Mathematics – School of Business Administration in Karvina
Contact Person: Mgr. Radmila Krkošková, Ph.D.
Timetable
Tue 17. 2. 13:55–14:15 A407
Prerequisites (in Czech)
FAKULTA(OPF) && TYP_STUDIA(B) && (FORMA(P) || FORMA(Z))
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 10 student(s).
Current registration and enrolment status: enrolled: 1/10, only registered: 4/10
fields of study / plans the course is directly associated with
Learning outcomes
The student knows the basic concepts of statistics such as population and sample, statistical variable, quantitative and qualitative variables, etc. The student is able to determine measures of central tendency: arithmetic mean, median, and mode. The student can determine measures of variability and concentration such as standard deviation, variance, skewness, and kurtosis. The student is able to formulate null and alternative hypotheses and test them using an appropriate statistical test (e.g., a two-sample t-test with equal variances). The student can also use nonparametric tests such as the chi-square test. The student is able to fit a line or another curve to data points in a graph and determine the statistical significance of a regression model. The student can calculate Pearson’s and Spearman’s correlation coefficients and interpret them. The student understands the concept of a time series, can decompose it into components, and determine the trend component. The student is able to apply ANOVA to test the equality of means of three or more samples. The student can quantify Taguchi loss functions. The student is able to design, apply, and interpret a factorial experiment.
Syllabus
1. Elementary Statistical Terms and Methods
Measures of central tendency, measures of variability, skewness, kurtosis, statistical sample with two variables, hypothesis testing in general.
2. Hypothesis Testing in Marketing – Parametric and Nonparametric Tests
A marketing study, what hypothesis testing brings in marketing, one-sample t-test, two-sample t-test - the nonpaired and paired versions. Testing median, the chi-squared test for one sample, two-sample tests, the chi-squared test for two samples, Mann's-Whitney's test, Wilcoxon's paired test.
3. Regression and Correlation Analysis
The concept of regression, estimation of regression coefficients, testing significance of regression coefficients, confidence intervals for regression coefficients, testing model significance. Correlation coefficient, correlation index, Spearman's (rank) correlation, multivariate linear dependence - relations for two explanatory variables.
4. Methods of Prediction
Introduction to time series analysis, analysis of trends, analysis of seasonality, model of constant seasonality, analysis of the random component of a regression model, testing properties of the random term, predictions, causal and prognostic methods.
5. Analysis of Variance (ANOVA)
One-factor ANOVA, a measure of dependence. ANOVA for two factors and three factors (Latin squares).
6. Experimental Plans
Full experimental plans: foundations of experimenting and its applications, experimental procedure, factor effect, factor significance, testing factor significance, graphical assessment of factor effect, graphs of interactions, modelling experiment. Fractional plans: graphical evaluation of factor effect in fractional plans. Two-level fractional plans, half plans, graphical method.
7. Taguchi's Methods
Taguchi's methods: loss functions, definition and properties of loss functions, loss function for various types of tolerances, total quality costs, monitoring quality costs, control charts.
Language of instruction
English
Further Comments
Study Materials
The course is also listed under the following terms Winter 2021, Summer 2022, Summer 2025.
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