Course for international guest/part time students

Faculty

Faculty of Science

Organization

TTK Department of Physical and Applied Geology

Code

ktudhksz1g17gm

Title

Advanced calculations in environmental science 1.

Usual semester

Autumn

Published semester

2026/27/1

ECTS

3

Language

en

Learning outcomes

The aim of the course is for students to acquire the theoretical foundations of probability theory, statistical inference, and time series analysis, and to become capable of applying these methods in practice to solve environmental science problems. During the training, students will learn the methods of estimation theory, hypothesis testing, correlation and univariate regression analysis, as well as the fundamentals of time series theory. The course develops analytical thinking, problem-solving skills, and the ability to perform independent data analysis (e.g., using basic Excel functions), and lays the groundwork for future script-based data analysis.

Course content

In the first half of the semester, students receive a comprehensive theoretical foundation: the main concepts and rules of probability theory, the methods of estimation theory (point and interval estimation), the principles and steps of hypothesis testing, and the theory and practical interpretation of correlation and regression analysis. All of these are illustrated using real environmental measurement data, with an emphasis on data quality control and the interpretation of results. In the second half of the semester, students learn techniques for creating distance matrices, the operation of the IF and VLOOKUP functions, as well as the handling and sorting of simpler data tables. The focus is on practicing basic data manipulation operations, the accurate application of formulas, and recognizing logical relationships within data. Later, in addition to more complex applications of the VLOOKUP function, students perform auto- and cross-correlation analyses as well as advanced time series analyses (separating trend, periodic, and noise components in groundwater level time series). Through these tasks, students work with real environmental datasets, independently solve statistical and data management problems, and gain hands-on experience in applying theoretical knowledge to practice. By the end of the course, students will be able to independently prepare, analyze, and interpret measurement data, identify potential sources of error, and select and apply the appropriate statistical methods to answer their research questions.

Assessment method

Colloqvivm

Bibliography

József Kovács, Péter Tanos, János Korponai, Ilona Kovácsné Székely, Károly Gondár, Katalin Gondár-Sőregi and István Gábor Hatvani (2012). Analysis of Water Quality Data for Scientists, Water Quality Monitoring and Assessment, Dr. Voudouris (Ed.), ISBN: 978-953-51-0486-5, InTech, DOI: 10.5772/32173. Békés Gábor és Kézdi Gábor (2024) Adatelemzés üzleti, közgazdasági és szakpolitikai döntésekhez. Alinea Kiadó, Budapest. Fordította Rózsás Sarolta

Programmes of the course