BA_ASt Applied Statistics

University of Finance and Administration
Winter 2023
Extent and Intensity
2/1/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
Ing. Jana Galvis Rivera (seminar tutor)
Ing. Hana Lipovská, Ph.D. (seminar tutor)
Guaranteed by
Ing. Hana Lipovská, Ph.D.
Department of Computer Science and Mathematics – Departments – University of Finance and Administration
Contact Person: Dita Egertová
Timetable of Seminar Groups
BA_ASt/cECPH: each even Wednesday 19:15–19:59 E305, each even Wednesday 20:00–20:45 E305, except Wed 15. 11. ; and Tue 5. 12. 15:45–17:15 E307, J. Galvis Rivera
BA_ASt/cMCPH: each even Wednesday 17:30–18:14 E304, each even Wednesday 18:15–19:00 E304, except Wed 15. 11. ; and Mon 4. 12. 17:30–19:00 E307, J. Galvis Rivera
BA_ASt/pECMCPH: each even Monday 14:00–14:44 E007KC, each even Monday 14:45–15:30 E007KC, each even Monday 15:45–16:29 E007KC, each even Monday 16:30–17:15 E007KC, H. Lipovská
Prerequisites
Basic knowledge of mathematics at the secondary school level and knowledge of the English language at least at the B2 level.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The aim is to prepare the student for formulating and testing the hypotheses of seminar, bachelor's and diploma theses and familiarization with traditional software tools, data visualization tools and the implementation of AI.
Learning outcomes
After completing the course, the student will be able to interpret the results of statistical surveys and graphic displays. He will be able to prepare basic and advanced statistics, graphical and tabular outputs from data files. Can process data using advanced office software and present it in a neat and understandable form. He will be able to prepare assignments for the implementation of complex surveys and investigations. He will recognize misleading and incorrect interpretations of the results, he will be able to explain how to correct them using mathematical statistics. He will know position indicators and variability indicators, he will be able to work with absolute and relative frequency, compile, use and interpret contingency tables. He will be able to perform correlation analysis and interpret its results. With the help of the software, he will be able to perform least squares linear regression estimation, be able to interpret the results and be aware of the pitfalls of this approach. He will know the official data sources and look for the necessary statistics in them.
Syllabus
  • 1. Graphical display of data. 2. Official statistical databases, data sources and working with them. 3. Basic statistical concepts. 4. Word variable data processing. 5. Elementary processing of data on numerical variables, quantiles. 6. Characterizing the position of values of a numeric variable. 7. Characterizing the variability of the values of a numerical variable. 8. Correlation coefficient, interpretation, pitfalls of Pearson's correlation coefficient. 9. Basic errors in data interpretation. 10. p-value, its interpretation and pitfalls 11. Linear regression, method of least squares Coefficient of determination, its interpretation and pitfalls
Literature
    required literature
  • FIELD, A. P., Discovering Statistics Using SPSS: (and Sex and Drugs and Rock 'n' Roll). SAGE, 2020. ISBN 9789351500827. 915 p.
    recommended literature
  • Harford, T. 2020. How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers. Hachette UK. ISBN 9781408712221, 352 p.
  • Blauw, S. 2021. The Number Bias. Hodder And Stoughton Ltd. ISBN: 1529342775. 175 p
Teaching methods
Lectures, exercises, preparation of projects.
Assessment methods
Credit – the student submits a complete proposal of a statistical research method for a problem of his choice. He will defend his proposal in a presentation at the seminar. Exam: oral - the student a) interprets a graph from real practice, identifies its weak points and suggests improvements, b) answers 2 theoretical questions c) demonstrates the ability to work with a data set.
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: 12 hodin KS/semestr.
The course is also listed under the following terms Winter 2024.
  • Enrolment Statistics (Winter 2023, recent)
  • Permalink: https://is.vsfs.cz/course/vsfs/winter2023/BA_ASt