INMBPSME Statistical Methods for Economists

School of Business Administration in Karvina
Winter 2024
Extent and Intensity
2/1/0. 5 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
Mon 10:35–12:10 B207
  • Timetable of Seminar Groups:
INMBPSME/01: Mon 13:55–14:40 B208, J. Mazurek
INMBPSME/02: Mon 14:45–15:30 B208, J. Mazurek
Prerequisites
FAKULTA(OPF) && TYP_STUDIA(B) && FORMA(P) && !NOWANY( INMNASDP Statistical Data Processing || INMNASTZ Statistical Data Processing )
There are no prerequisites for the subject.
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 60 student(s).
Current registration and enrolment status: enrolled: 12/60, only registered: 0/60
fields of study / plans the course is directly associated with
Course objectives
The objective is to provide a deeper insight into statistical methods suitable for multivariate data analysis, provide theoretical tools for the selected methods, and teach how to apply them, using a computer. The subject also presents special mathematical methods applied in economics, the methods being an indispensable part of modern management. Students learn the methods in such a way that they are able to apply them in marketing, and they also learn to control production quality in all stages of a production process, i.e. in the pre-production, production and the post-production stage.
Syllabus
  • 1. Elementary statistical terms and methods
    2. Hypothesis testing in marketing - parametric tests
    3. Hypothesis testing in marketing - nonparametric tests
    4. Regression analysis
    5. Correlation analysis
    6. Analysis of variance
    7. Analysis of variance: two factors and Latin squares
    8. Full experimental plans
    9. Fractional experimental plans
    10. Two-level fractional plan
    11. Taguchi's methods: loss functions
    12. Taguchi's methods: total quality costs
    13. Methods of sales prediction
    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 tests
    A marketing study, what hypothesis testing brings in marketing, one-sample t-test, two-sample t-test - the nonpaired and paired versions.
    3. Hypothesis testing in marketing - nonparametric tests
    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.
    4. Regression analysis
    The concept of regression, estimation of regression coefficients, testing significance of regression coefficients, confidence intervals for regression coefficients, testing model significance.
    5. Correlation analysis
    Correlation coefficient, correlation index, Spearman's (rank) correlation, multivariate linear dependence - relations for two explanatory variables.
    6. Analysis of variance (ANOVA)
    One-factor ANOVA, a measure of dependence.
    7. Analysis of variance (ANOVA): two factors and Latin squares
    Two factors, three factors (Latin squares).
    8. 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.
    9. Fractional plans
    Graphical evaluation of factor effect in fractional plans.
    10. Two-level fractional plan
    Half plans, graphical method.
    11. Taguchi's methods: loss functions
    Definition and properties of loss functions, loss function for various types of tolerances.
    12. Taguchi's methods: total quality costs
    Monitoring quality costs, control charts.
    13. Methods of sales prediction
    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.
Literature
    required literature
  • RAMÍK, J., STOKLASOVÁ, R., TOŠENOVSKÝ, J. Statistické metody pro ekonomy. Karviná: OPF SU, 2003. ISBN 80-85943-63-8. info
    recommended literature
  • DANIEL, W. W., TERREL, J. Business statistics for management and economics. Houghton Mifflin, 2005. ISBN 978-03957-280-25. info
  • BLECHARZ, P. Základy metody DOE (Taguchiho přístup). Ostrava : REPRONIS, 2005. ISBN 80-7329-106-1. info
  • TOŠENOVSKÝ, J. Průvodce hodnocením způsobilosti. Ostrava, 2003. info
  • TOŠENOVSKÝ J., NOSKIEVIČOVÁ, D. Statistické metody pro zlepšování jakosti. Ostrava : Montanex, 2000. ISBN 80-7225-040-X. info
  • VAN MATRE, J. G., GILBREATH, G. H. Statistics for Business and Economics. BPI/IRWIN, Homewood, 1997. ISBN 0-256-03719-1. info
Teaching methods
Skills demonstration
Seminar classes
At least 70% seminar attendance is required.
Assessment methods
Written exam/Written test. To pass the exam at least 60 points is needed from the test (100 points) plus bonus points for seminar activity (max. 10 points).
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
Teacher's information
In-seminar tests, 70% attendance in seminars; the form of the exam: written test.
Activity Difficulty [h]
Ostatní studijní zátěž 66
Přednáška 26
Seminář 13
Zkouška 40
Summary 145
The course is also listed under the following terms Winter 2014, Winter 2015, Winter 2016, Winter 2017, Winter 2018, Winter 2019, Winter 2020, Winter 2021, Summer 2022, Winter 2022, Winter 2023.
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