B_PrSt Statistics and Probability

University of Finance and Administration
Winter 2024
Extent and Intensity
2/1/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
PaedDr. Renata Majovská, PhD. (seminar tutor)
Guaranteed by
PaedDr. Renata Majovská, PhD.
Department of Computer Science and Mathematics – Departments – University of Finance and Administration
Contact Person: Ivana Plačková
Timetable of Seminar Groups
B_PrSt/cAPH: each odd Tuesday 15:45–16:29 E225, each odd Tuesday 16:30–17:15 E225, except Tue 8. 10. ; and Tue 15. 10. 15:45–17:15 E306, R. Majovská
B_PrSt/cFPH: each odd Tuesday 17:30–18:14 E303PC, each odd Tuesday 18:15–19:00 E303PC, except Tue 8. 10. ; and Tue 15. 10. 17:30–19:00 E306, R. Majovská
B_PrSt/pAFPH: Wed 10:30–11:14 E004, Wed 11:15–12:00 E004, R. Majovská
B_PrSt/vAPH: Sat 5. 10. 14:00–15:30 E303PC, 15:45–17:15 E303PC, Sat 16. 11. 9:45–11:15 E303PC, 11:30–13:00 E303PC, Sat 14. 12. 9:45–11:15 E303PC, 11:30–13:00 E303PC, R. Majovská
Prerequisites
There are no prerequisites for this course.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
After completing the course students will be able to use basic terms of descriptive statistics. They will understand the problems of statistical surveys and will be able to process data. They will know the differences between simple and interval frequency distribution (including graphical representation of the frequency distribution). Students will be able to measure the parameters of location, variability, skewness and kurtosis of frequency distribution.
They will be able to use the basic terms of probability theory, calculate the empirical and theoretical probability, create tree diagrams, Venn diagrams, use properties of probability numbers, the Law of large numbers. In the field of random variable, students will know some discrete and continous probability distributions.
Learning outcomes
After completing the course, a student will be able to:
- process and analyse quantitative and qualitative data
- find characteristics of location and variability, coefficient of correlation
- calculate probability.
Syllabus
  • 1. Definition of Statistics, history of Statistics, Data classification, Data collection and design of a statistical study
  • 2. Descriptive Statistics: Data processing of verbal variable
  • 3. Data processing of numerical variable (a small data set), Measures of central tendency, variability
  • 4. Skewness, kurtosis, quantiles, Box plot
  • 5. A frequency distribution, Intervals
  • 6. Measures of central tendency and variability (a large data set)
  • 7. Skewness, kurtosis (a large data set), The Empirical rule and Testing for Normality, Chebyshev’s theorem
  • 8. Linear correlation, Linear regression
  • 9. Probability: Probability of an event, empirical, theoretical, subjective probability, Properties of probability numbers, Law of large numbers
  • 10. Conditional probability, rules of probability, mutually exclusive events, Independent events
  • 11. Random variable, probability and distribution function, characteristics of random variables
  • 12. Examples of distributions of discrete and continuous type, central limit theorem
Literature
    required literature
  • BÍLKOVÁ, Diana, Petr BUDINSKÝ and Václav VOHÁNKA. Pravděpodobnost a statistika (Probability and Statistics). 1. vydání. Plzeň: Vydavatelství a nakladatelství Aleš Čeněk, s.r.o, 2009, 658 pp. ISBN 978-80-7380-224-0. info
  • ŘEZANKOVÁ, Hana, Tomáš LÖSTER a Zdeněk ŠULC. Úvod do statistiky. Vydání 2. přepracované. Praha: Oeconomica, 2019. Vysokoškolská skripta. ISBN 978-80-245-2301-9.
  • NEUBAUER, Jiří, Marek SEDLAČÍK a Oldřich KŘÍŽ. Základy statistiky: aplikace v technických a ekonomických oborech. 3., rozšířené vydání. Praha: Grada Publishing, 2021. ISBN 978-80-271-3421-2.
    recommended literature
  • SVOBODA, Milan, Mikuláš GANGUR a Kateřina MIČUDOVÁ. Statistické zpracování dat. Plzeň: Západočeská univerzita v Plzni, 2019. ISBN 978-80-261-0883-2.
  • KOŠŤÁKOVÁ, Tereza. O složitém jednoduše, aneb, Nebojte se statistiky, nekouše. Ilustroval Tomáš ZIMA. Praha: Český statistický úřad, 2019. ISBN 978-80-250-2908-4.
  • ARLTOVÁ, Markéta, Diana BÍLKOVÁ and ET AL. Sbírka příkladů ze statistiky. Statistika A. Praha: Oeconomica, 2000, 272 pp. ISBN 80-7079-727-4. info
Teaching methods
Lectures and seminars in full-time study; tutorials in part-time study; compulsory seminar participation is 75 % in full-time study, compulsory tutorial participation is 50 % in part-time study. MS Excel is used to solve problems.
Students with ISP have the same duties. Compulsory attendance is not required.
Assessment methods
The course is completed with a credit and exam.
Credit:
- 1 written test, it is necessary to obtain at least 50 % of points from the test;
- 1 semester work or completion of partial tasks assigned by the teacher in the exercise,
Exam:
- 1 written test, it is necessary to obtain at least 60 % of points from the test;
- oral examination: student will answer 2 theoretical questions;
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
Information on the extent and intensity of the course: 12 hodin KS/semestr.
Teacher's information
Mathematical knowledge within the scope of university mathematics is a prerequisite for mastering the content of this subject.
The course is also listed under the following terms Winter 2016, Winter 2017, Winter 2018, Winter 2019, Winter 2020, Winter 2021, Winter 2022, Winter 2023.
  • Enrolment Statistics (recent)
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