| Course Unit Code | 151-0005/02 |
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| Number of ECTS Credits Allocated | 6 ECTS credits |
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| Type of Course Unit * | Choice-compulsory |
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| Level of Course Unit * | First Cycle |
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| Year of Study * | |
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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 | English |
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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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| FRI02 | doc. Ing. Václav Friedrich, Ph.D. |
| Summary |
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| This subject presents an introductory course into statistics. It introduces the basic concepts and methods of probability theory, descriptive statistics and statistical induction. The aim is to learn how to present and analyze statistical data and properly interpret the results. |
| Learning Outcomes of the Course Unit |
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- Students will be introduced to statistics as a modern discipline that focuses on random and mass phenomena and processes.
- Students will become familiar with the basic concepts of probability theory, descriptive and inductive statistics.
- Students will learn to use basic statistical methods and tools and discover how these methods can be used to solve economic problems.
- Students will be able to process data on the computers and present the results of analyses in the form of tables, graphs and statistics.
- Students will be able to use the acquired knowledge in other subjects of the Bachelor's study and in processing data for seminar and Bachelor's theses. |
| Course Contents |
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1. Statistics and statistical thinking
2. Presentation of statistical data
3. Descriptive statistics of categorical data
4. Descriptive statistics of numerical data
5. Pooled and interval data
6. Association, contingency tables
7. Correlation and regression, time series
8. Probability and probability calculations
9. Conditional probability, decision trees
10. Random variable and probability distribution
11. Normal distribution, limit theorems
12. Basics of statistical induction |
| Recommended or Required Reading |
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| Required Reading: |
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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.
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.
TAYLOR, Sonia. Business Statistics for Non-Mathematicians. 2nd Edition. New York: Palgrave Macmillan, 2007. 368 p. ISBN 978-0-230-50646-6. |
HENDL, Jan; SIEGL, Jakub a MOLDAN, Martin. Základy matematiky, logiky a statistiky pro sociologii a ostatní společenské vědy v příkladech. 3. vydání. Praha: Univerzita Karlova, nakladatelství Karolinum, 2022. 570 s. ISBN 978-80246-5400-3.
JANÁČEK, Julius. Statistika jednoduše: Průvodce světem statistiky. Praha: Grada, 2022. 120 s. ISBN 978-80-271-1738-3.
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. |
| 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.
COHEN, Louis and HOLLIDAY, Michael. Practical Statistics for Students: An Introductory Text. 2nd Edition. London: SAGE Publications, 1996 (reprinted 2013). 384 p. ISBN 978-1853963292.
MOHR, Donna L.; WILSON, William J. and FREUND, Rudolf J. Statistical Methods. 4th Edition. London: Elsevier, 2021. 784 p. ISBN 978-0128230435. |
HENDL, Jan. Přehled statistických metod: Analýza a metaanalýza dat. 5. rozšířené vydání. Praha: Portál, 2015. 736 s. ISBN 978-80-262-0981-2.
MAREK, Luboš a kol. Statistika v příkladech. 2. vydání. Praha: Professional Publishing, 2016. 404 s. ISBN 978-80-7431-153-6.
CAMM, Jeffrey D. et al. Statistics for Business and Economics. 15th Edition. Boston: Cengage Learning, 2023. 1120 p. ISBN 978-0357715857. |
| Planned learning activities and teaching methods |
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| Lectures, Tutorials |
| Assesment methods and criteria |
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| Tasks are not Defined |