Course: Selected Aspects of Applied Mathematics 2

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Course title Selected Aspects of Applied Mathematics 2
Course code KMA/VKAM2
Organizational form of instruction Lecture + Tutorial
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 2
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Dostal Rostislav, Ing. Ph.D.
Course content
1. Introduction to statistical methodology.   2. Overview of statistical computing environments.   3. Basic statistical data processing I (data types, characteristics of position and variability).   4. Advanced statistical data processing II (other characteristics).   5. Basic graphical presentation of biomedical data.   6. Advanced graphical presentation of biomedical data.   7. Fundamentals of probability theory.   8. Discrete random variable.   9. Continuous random variable. 10. Basic probabilistic models. 11. Analysis of categorical data (pivot tables).

Learning activities and teaching methods
Interactive lecture, Task-based study method, Students' self-study, Practicum
  • Contact hours - 22 hours per semester
  • Preparation for comprehensive test (10-40) - 30 hours per semester
prerequisite
Knowledge
Students should be familiar with basic notions of mathematics to the extent of the course KMA/VKAN1.
Skills
Control the user-level MS Excel.
Critically evaluate data sources with emphasis on reliability and completeness.
Competences
N/A
learning outcomes
Knowledge
Use selected SW for statistical processing of biomedical data. Apply statistical principles to selected real problems and propose solutions in selected SW. Interpret the statistic results.
Skills
Apply theoretical knowledge of probability in SW Excel (or in other statistically oriented software).
Utilize knowledge of basic statistical methods and procedures for data analysis in sw Ecxel (or in other statistically oriented software)
Competences
N/A
N/A
teaching methods
Knowledge
Interactive lecture
Practicum
Task-based study method
Self-study of literature
Skills
Interactive lecture
Practicum
Task-based study method
Self-study of literature
Competences
Interactive lecture
Practicum
Task-based study method
Self-study of literature
assessment methods
Knowledge
Skills demonstration during practicum
Seminar work
Skills
Skills demonstration during practicum
Seminar work
Competences
Skills demonstration during practicum
Seminar work
Recommended literature
  • HENDL J. Přehled statistických metod zpracování. PRAHA, 2006. ISBN 80 7367-123-9.
  • Kožíšek, Jan; Stieberová, Barbora. Statistika v příkladech : praktické aplikace řešené v MS Excel. Praha : Verlag Dashöfer, 2012. ISBN 978-80-86897-48-6.
  • Reif. Metody matematické statistiky. ZČU Plzeň, 2000.
  • ZVÁROVÁ J. Základy statistiky pro biomedicíncké obory. PRAHA, 2002. ISBN 80-246-0609-7.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester