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Lecturer(s)
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Urbánek Tomáš, Ing. Ph.D.
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Metzker Zdenko, Ing. Ph.D.
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Kunčar Aleš, Ing.
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Course content
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- Introduction to a questionnaire survey and hypotheses - Import and cleaning of data before analysis in MS Excel - Descriptive statistics in MS Excel - T-tests in MS Excel - ANOVA + post-hoc tests in MS Excel - Introduction to programming in R - Working with dataframes in R - Descriptive statistics in R - Basic statistical tests in R - Association tests in R
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Learning activities and teaching methods
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Lecturing, Exercises on PC, Practice exercises
- Home preparation for classes
- 13 hours per semester
- Participation in classes
- 26 hours per semester
- Preparation for course credit
- 36 hours per semester
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| learning outcomes |
|---|
| Knowledge |
|---|
| Defines the principle of questionnaire survey |
| Defines the principle of questionnaire survey |
| Clarifies the differences between data types |
| Clarifies the differences between data types |
| Defines the principle of statistical hypothesis testing |
| Defines the principle of statistical hypothesis testing |
| Explains the principle of basic statistical tests |
| Explains the principle of basic statistical tests |
| Clarifies the concept of data reporting |
| Clarifies the concept of data reporting |
| Skills |
|---|
| Develops research questions and hypotheses |
| Develops research questions and hypotheses |
| Develops a questionnaire survey |
| Develops a questionnaire survey |
| Decides which statistical test is appropriate for statistical hypothesis testing |
| Decides which statistical test is appropriate for statistical hypothesis testing |
| Applies software for evaluation of statistical test |
| Applies software for evaluation of statistical test |
| Interprets the results of a statistical test |
| Interprets the results of a statistical test |
| teaching methods |
|---|
| Knowledge |
|---|
| Practice exercises |
| Lecturing |
| Practice exercises |
| Exercises on PC |
| Exercises on PC |
| Lecturing |
| assessment methods |
|---|
| Analysis of the student's performance |
| Grade (Using a grade system) |
| Analysis of the student's performance |
| Grade (Using a grade system) |
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Recommended literature
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Barilla, J., Simr, P., Sýkorová, K. Microsoft Excel 2016: podrobná uživatelská příručka. Brno: Computer Press, 2016. ISBN 978-80-251-4838-9.
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Barilla, Jiří. Microsoft Excel pro techniky a inženýry. Vyd. 1. Brno : Computer Press, 2008. ISBN 978-80-251-2421-5.
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Brož, M., Bezvoda, V. Microsoft Excel 2007/2010: vzorce, funkce, výpočty. Brno: Computer Press, 2011. ISBN 978-80-251-3267-8.
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Curwin,J., Slater,R., Eadson,D. Quantitative Methods for Business Decisions. 7th ed. Andover, UK, Cengage Learning, 2013. ISBN 978-1-480-6012-4.
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Knight, Gerald. Analyzing business data with Excel [elektronický zdroj]. Sebastopol, CA : O´Reilly Media, 2006. ISBN 978-0-596-10073-5.
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Laurenčík, M. Excel - pokročilé nástroje: funkce, makra, databáze, kontingenční tabulky, prezentace, příklady. Praha: Grada, 2016. ISBN 978-80-247-5570-0.
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MacDonald, Matthew. Excel 2007 [elektronický zdroj] : the missing manual. Sebastopol, CA : Pogue Press/O´Reilly, 2007. ISBN 978-0-596-52759-4.
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NAVARRŮ, Miroslav. Excel 2019: podrobný průvodce uživatele. http://www.grada.cz/excel2019. Praha: Grada Publishing, 2019. ISBN 978-80-247-2026-5.
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Triola, Mario F. Elementary statistics using Excel. 4th ed. Boston : Addision-Wesley, 2010. ISBN 978-0-321-56496-2.
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