PřF:C7879 Exp. data process - Course Information

C7879 Experimental data processing

Faculty of Science
Spring 2024

Extent and Intensity

1/0/0. 1 credit(s) (plus 2 credits for an exam). Type of Completion: zk (examination).

Teacher(s)

Mgr. Kateřina Dadáková, Ph.D. (lecturer)

Guaranteed by

Timetable

Mon 19. 2. to Sun 26. 5. Tue 9:00–9:50 B11/205

Prerequisites

C4222 Basic calculations
C4222

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 aim is the application of principal data processing and visualisation on concrete data sets.

Learning outcomes

The student will be able to remove outliers from a data set, to assess the distribution, and to perform the most suitable visualisation.

Syllabus

1.Basic characteristics of experimental data, 2. General procedure of data processing, 3.-5. Processing and visualisation of qualitative data sets, 6.-8. Processing and visualisation of quantitative data sets, 9.-11. Processing and visualisation of practice data sets, 12. Summary

Literature

HOLČÍK, Jiří and Martin KOMENDA. Matematická biologie: e-learningová učebnice [online]. (Mathematical Biology: e-learning textbook [on/line]). 1st ed. Brno: Masarykova univerzita, 2015. ISBN 978-80-210-8095-9. URL info

Teaching methods

Lectures with concrete examples students can try to solve using their own computers.

Assessment methods

The grade is based on the level of practice data sets processed by the student.

Language of instruction

Czech

Further Comments

Study Materials
The course can also be completed outside the examination period.
The course is taught annually.

The course is also listed under the following terms Spring 2022, Spring 2023, Spring 2025.