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Lecturer(s)
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Svoboda Milan, Ing. Mgr. Ph.D.
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Mičudová Kateřina, Ing. Ph.D.
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Gangur Mikuláš, Doc. RNDr. Ph.D.
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Tesařová Vendula, Ing. Ph.D.
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Říhová Pavla, Ing. Ph.D.
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Course content
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Empirical research, hypothesis, planing and steps of research Data sources for research, techniques of data gathering Introduction to hypothesis testing, type 1 and type 2 errors, interpretation of results, test validity and reliability Normality tests (chí-square, Liliefors test, graphical tests,), independence in contingency table, Chi-square test for independence. One-sample tests (mean, variance, standard deviation) relation to interval estimation Two-sample tests (means equity, variances equity, relative frequncies equity, paired two-sample test) One factor ANOVA Fundamentals of regression and correlation analysis.
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Learning activities and teaching methods
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Lecture with practical applications, Individual study, Self-study of literature, Practicum
- unspecified
- 22 hours per semester
- Preparation for an examination (30-60)
- 30 hours per semester
- Contact hours
- 52 hours per semester
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| prerequisite |
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| Knowledge |
|---|
| apply basic knowledge of statistic (KEM/STA). |
| Skills |
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| determine characteristics of statistics file. |
| determine quantiles of random variable. |
| work in MS Excel. |
| Competences |
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| N/A |
| N/A |
| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| explain and use methods of real data processing. |
| use software for data processing. |
| make interpretation and prezentation of data. |
| Skills |
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| assemble the research plan. |
| assemble questionaire for research. |
| make the suitbale random selection from population. |
| formulate research hypothesis and statisticaly evaluate them. |
| determkine distribution parameters using statistical test. |
| realize the test of mean equivalence for two or more samples. |
| decide about normality of data. |
| realize chi square in contingency table. |
| use statistical software for analyzing and statistical evaluation of data. |
| Competences |
|---|
| N/A |
| N/A |
| teaching methods |
|---|
| Knowledge |
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| Practicum |
| Self-study of literature |
| Individual study |
| Interactive lecture |
| E-learning |
| Task-based study method |
| Skills |
|---|
| Practicum |
| Individual study |
| Discussion |
| Project-based instruction |
| E-learning |
| Task-based study method |
| Competences |
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| Lecture supplemented with a discussion |
| Individual study |
| Task-based study method |
| E-learning |
| assessment methods |
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| Knowledge |
|---|
| Written exam |
| Test |
| Seminar work |
| Practical exam |
| Skills |
|---|
| Skills demonstration during practicum |
| Practical exam |
| Project |
| Seminar work |
| Competences |
|---|
| Practical exam |
| Project |
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Recommended literature
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Box, E. P. George, Jenkins, M. Gwilym, Reinsel, C. Gregory. Time Series Analysis: Forecasting and Control. WILEY, 2008. ISBN 978-0-470-27284-8.
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Hair, F. Joseph, Black, C. William, Babin, J. Barry, Anderson E. Rolph. Multivariate Data Analysis. Prentice-Hall, 2010. ISBN 978-0-13-813263.
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Hendl, Jan. Přehled statistických metod zpracování dat : analýza a metaanalýza dat. Vyd. 2., opr. Praha : Portál, 2006. ISBN 80-7367-123-9.
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Pecáková, Iva. Statistika v terénních průzkumech. 2., dopl. vyd. Praha : Professional Publishing, 2011. ISBN 978-80-7431-039-3.
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Řezanková, Hana. Analýza dat z dotazníkových šetření. 3., aktualiz. vyd. Praha : Professional Publishing, 2011. ISBN 978-80-7431-062-1.
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Řezanková, Hana. Analýza kategoriálních dat. Vyd. 1. Praha : Oeconomica, 2005. ISBN 80-245-0926-1.
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