Course for international guest/part time students

Faculty

Faculty of Science

Organization

TTK Department of Meteorology

Code

metstatkl0g22gm

Title

Statistical climatology (practice)

Usual semester

Spring

Published semester

2025/26/2

ECTS

1

Language

hu

Learning outcomes

The main goal is to prepare statistical climatological studies by using programming language. Competencies: Knowledge: Basic knowledge of the R programming language acquired during BSc studies. Knowledge: The student is able to perform simple programming and data processing tasks. Attitude: The student acquires practical knowledge in the field of data processing. Autonomy and Responsibility: With the knowledge gained in the practice course, the student becomes able to handle data arrays, perform basic statistical operations on them, and visualize the results.

Course content

Handling objects in the R programming language. Manage text files, tables and three- or multidimensional data arrays, perform calculations with their data, display derived time series and fields.

Assessment method

Practical exercises and written exam (5 levels)

Bibliography

Chang, W. (2013): R Graphics Cookbook: Practical Recipes for Visualizing Data. O’Reilly Media, Inc., Beijing, Cambridge, Farnham, Köln, Sebastopol, Tokyo Wickham, H., Grolemund, G. (2017): R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media, Inc., Beijing, Cambridge, Farnham, Köln, Sebastopol, Tokyo

Programmes of the course