BA_PrSt Probability and Statistics

University of Finance and Administration
Winter 2019
Extent and Intensity
2/1/0. 5 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
BA_PrSt/cBMPH: each odd Wednesday 17:30–18:14 E225, each odd Wednesday 18:15–19:00 E225, R. Majovská
BA_PrSt/pBMPH: Wed 15:45–16:29 E225, Wed 16:30–17:15 E225, 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, process data, know the differences between simple and interval frequency distribution and they will also recognize, in which case the simple frequency distribution is used for representation of the frequency distribution and in which case the interval frequency distribution (including graphical representation of the frequency distribution). Students will be able to measure the location, variability, skewness and kurtosis of frequency distribution. They will be able to use the basic terms of probability theory, the operations with random phenomena and the principles of computation of probability random phenomenon. In the field of random variable, students will know some discrete and continuous probability distributions and the selected limit theorems. They will know the definition of random sample.
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,
- work with random variable.
Syllabus
  • 1. Basic statistical terms
  • 2. Data processing of verbal variable
  • 3. Data processing of numeric variable, quantiles
  • 4. Location characterizing of values of numerical variable
  • 5. Variability characterizing of values of numerical variable
  • 6. Concentration characterizing of values of numerical variable
  • 7. Random phenomenon
  • 8. Random variable
  • 9. Some distribution of discrete type
  • 10. Some distribution of continuous type
  • 11. Some limit theorems
  • 12. Random sample, statistics
Literature
    required literature
  • ZÁŠKODNÝ, Přemysl. The Principles of Probability and Statistics (Data Mining Approach). Praha: Curriculum, 2012, 122 pp. ISBN 978-80-904948-6-2. info
  • Mario F. Triola. Elementary Statistics. Boston: Addison Wesley, 2003. 864 s. ISBN 0-8053-0271-9.
  • Hossein Pishro-Nik. Introduction to Probability, Statistics, and Random Processes. New York: Karra Research LLC, 2014. 731 s. ISBN 978-0990637202.
    recommended 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
Teaching methods
Lectures and seminars in full-time study; tutorials in part-time study; data-projector is used in teaching; MS Excel will be presented to the students. Minimum mandatory attendance at seminars in full-time is 75 %, at tutorials in part-time study 50 %.
Assessment methods
Course ending: Credit: 1 written test, it is necessary to obtain at least 50 % of points from the test; Exam: 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
English
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: 10 hodin KS/semestr.
The course is also listed under the following terms Winter 2016, Winter 2017, Winter 2018, Winter 2020, Winter 2021, Winter 2022.
  • Enrolment Statistics (Winter 2019, recent)
  • Permalink: https://is.vsfs.cz/course/vsfs/winter2019/BA_PrSt