UIINP19 Probability and Statistics

Faculty of Philosophy and Science in Opava
Summer 2023
Extent and Intensity
2/2/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
RNDr. Radka Poláková, Ph.D. (lecturer)
RNDr. Radka Poláková, Ph.D. (seminar tutor)
Guaranteed by
RNDr. Radka Poláková, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Timetable
Thu 16:25–18:00 H2
  • Timetable of Seminar Groups:
UIINP19/A: Thu 18:05–19:40 H2, R. Poláková
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course brings basic background to modern statistics which is used in public administration. The first goal of this course is to acquaint students with methodologies of data collecting followed by their processing as statistical files, basics of creating and reading statistical tables and charts, interpretation of descriptors of statistical files. Furthermore, the course also explains basis of regression and correlation analysis which represent basic descriptors to analysis relations among statistical data and practical using statistics to data analysis. Also are discussed the most important probabilistic models, chiefly normal distribution and statistical induction, problem of statistical hypothesis and finally principle time-series, their analysis, prediction and trends of indexing and data clustering.
Learning outcomes
Students will be able to:
- collect and process statistical data.
- compile and read statistical tables and graphs.
- interpret descriptive characteristics of statistical files.
Syllabus
  • 1. Basic statistical terms, statistical files, the role of data in statistics, quantitative data
  • 2. Basic operations in statistics, basic descriptors and their relation
  • 3. Regression and correlation analysis
  • 4. Elementary terms in probability theory
  • 5. Probabilistic models, basics of statistical induction and hypotheses testing
  • 6. Introduction to time-series and modern indexing methods
Literature
    required literature
  • AMC The School of Business. GNU PSPP Statistical Analysis Software. Step by Step Training Manual [online]. [cit. 2017-09-27]. Dostupné na: https://books.google.cz/books?id=pH21CgAAQBAJ&printsec=frontcover
    recommended literature
  • SEDLAČÍK, M., J. NEUBAUER a O. KŘÍŽ. Základy statistiky. 2. vyd. Praha: Grada, 2016. ISBN 978-80-247-5786-5. info
  • Otipka, P., Šmajstrla, V. PRAVDĚPODOBNOST A STATISTIKA. Ostrava, 2013. URL info
  • WALKER, Ian. Výzkumné metody a statistika. Praha: Grada, 2013. ISBN 978-80-247-3920-5. info
Teaching methods
Interactive lecture
Lecture with a video analysis
Assessment methods
75% attendance, active participation
Credit test, written exam
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is also listed under the following terms Summer 2020, Summer 2021, Summer 2022, Summer 2024, Summer 2025.
  • Enrolment Statistics (Summer 2023, recent)
  • Permalink: https://is.slu.cz/course/fpf/summer2023/UIINP19