| Course Unit Code | 151-0353/01 |
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| Number of ECTS Credits Allocated | 3 ECTS credits |
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| Type of Course Unit * | Compulsory |
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| Level of Course Unit * | First Cycle |
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| Year of Study * | Third Year |
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| Semester when the Course Unit is delivered | Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| S1A20 | prof. RNDr. Dana Šalounová, Ph.D. |
| Summary |
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| The aim of the subject is to train students in the practical processing of statistical data. The choice of methods is oriented towards the processing of files obtained in marketing or other economic research, mainly for the needs of bachelor theses. The course is based on the knowledge of basic statistics (Statistics for Economists or Statistics A). The software used is MS Excel with the Real Statistics add-in. |
| Learning Outcomes of the Course Unit |
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The subject builds on the knowledge gained in Statistics for Economists (Statistics A).
In this course students will
- learn how to create, edit, analyse, interpret and present data files;
- learn how to create descriptive statistics, perform first and second level classification and become familiar with selected statistical tests suitable for use in undergraduate theses;
- learn the basics of academic writing (guidelines and standards, IMRaD, citations, basic typography). |
| Course Contents |
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1. Data set, types of variables, data entry usin Excel, coding responses, missing values.
2. Continuous variables: descriptive statistics, boxplots, histograms.
3. Modifying the data file, transforming variables, split files, merge files.
4. Categorical variables: frequency tables, bar graphs, pie graphs.
5. Output processing, pivoting tables, editing charts and graphs.
6. Contingency tables, independence testing.
7. Principles of hypothesis testing, T-tests, the good-fit test.
8. Independece analysis, ANOVA.
9. Correlation.
10. Regression. |
| Recommended or Required Reading |
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| Required Reading: |
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FIELD, Andy. Adventure in Statistics: The Reality Enigma. Second Edition. Los Angeles: SAGE Publications, 2022. 664 p. ISBN 978-1529797138.
LIND, Douglas A.; MARCHAL, William G. and WATHEN, Samuel A. Basic Statistics in Business and Economics. 10th Edition. New York: McGraw-Hill Education, 2021. 640 p. ISBN 978-1260597578. |
JANÁČEK, Julius. Statistika jednoduše: Průvodce světem statistiky. Praha: Grada, 2022. 120 s. ISBN 978-80-271-1738-3.
HENDL, J. a kol. Základy matematiky, logiky a statistiky pro sociologii a ostatní společenské vědy v příkladech. Praha: Karolinum, 2022. ISBN 978-80-246-5400-3.
ZAIONTZ C. Real Statistics Using Excel Succinctly. [online] Morrisville: Syncfusion, 2015. ISBN 978-1-64200-078-8. Available from: https://www.syncfusion.com/succinctly-free-ebooks/statistics. |
| Recommended Reading: |
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CAMM, Jeffrey D. et al. Statistics for Business and Economics. 15th Edition. Boston: Cengage Learning, 2023. 1120 p. ISBN 978-0357715857.
SALKIND, Neil J. and FREY, Bruce B. Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel. Fifth Edition. London: SAGE Publications, 2021. 512 p. ISBN 978-1071803882. |
HENDL, Jan. Přehled statistických metod: Analýza a metaanalýza dat. 5. rozšířené vydání. Praha: Portál, 2015. 736 s. ISBN 978-80-262-0981-2.
RABUŠIC, Ladislav; SOUKUP,Petr a MAREŠ, Petr. Statistická analýza sociálněvědních dat (prostřednictvím SPSS). 2. přepracované vydání. Brno: Masarykova univerzita, 2019. 576 s. ISBN 978-80-210-9247-1.
SALKIND, Neil J. and FREY, Bruce B. Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel. Fifth Edition. London: SAGE Publications, 2021. 512 p. ISBN 978-1071803882. |
| Planned learning activities and teaching methods |
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| Lectures, Individual consultations, Tutorials, Other activities |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Exercises evaluation | Credit | 85 | 85 |