Environmental statistics and modelling Field of study: Aquamatics - Interdisciplinary Management of Water Environments
Programme code: W2-S2AQA24.2024

Module name: Environmental statistics and modelling
Module code: AQ_017
Programme code: W2-S2AQA24.2024
Semester: winter semester 2025/2026
Language of instruction: English
Form of verification: course work
ECTS credits: 6
Purpose and description of the content of education:
The course in Environmental Statistics and Modelling will provide the student with the skills to go on to a career in this exciting area. Students will learn how models of environmental processes are developed and applied across a range of areas including climate change and the analysis of biodiversity. Students will gain an appreciation of all aspects of environmental modelling ranging from the philosophy of model development, focussing on links to observations and uncertainty analysis, through to more practical aspects such as numerical approximation and algorithm development and testing. The course aims to complete and deepen the knowledge already acquired by students in the field of statistics during the three-year degree course, providing concepts and methodologies useful for environmental sciences, with particular attention to univariate statistics, and mentions of multivariate statistics and geostatistics.
List of modules that must be completed before starting this module (if necessary): not applicable
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
Knowledge on univariate statistics applied to spatial analysis: multiple way ANOVA, ANCOVA and regression, with particular attention to the variable selection methods. [01]
 AQ2_W01 [3/5] AQ2_W07 [3/5]
Knowledge on the fundamental elements of multivariate statistics and geostatistics. [02]
 AQ2_W01 [2/5] AQ2_U07 [2/5]
Knowledge on the basic principles of machine learning, with particular attention to neural networks and random forest [03]
 AQ2_W01 [4/5] AQ2_W07 [4/5]
Ability to apply ANOVA and regression to experimental and spatial data, using statistical software;. [04]
 AQ2_U02 [3/5]
Ability to correctly choose the most appropriate instruments for their own analysis, based on the possibility and limits of the various approaches available. [05]
 AQ2_U02 [4/5] AQ2_U03 [4/5]
Ability to carry out simple multivariate or geostatistical analyses [06]
 AQ2_U02 [2/5]
Form of teaching Number of hours Methods of conducting classes Assessment of the learning outcomes Learning outcomes
workshop [01] 60 Formal lecture/ course-related lecture [a01] 
Activating method – seminar / proseminar [b05] 
Laboratory exercise / experiment [e01] 
Project scheduling [e04]  		course work 01 02 03 04 05 06
The student's work, apart from participation in classes, includes in particular:
Name Category Description
Literature reading / analysis of source materials [a02] Preparation for classes
reading the literature indicated in the syllabus; reviewing, organizing, analyzing and selecting source materials to be used in class
Studying the literature used in and the materials produced in class [c02] Preparation for verification of learning outcomes
exploring the studied content, inquiring, considering, assimilating, interpreting it, or organizing knowledge obtained from the literature, documentation, instructions, scenarios, etc., used in class as well as from the notes or other materials/artifacts made in class
Analysis of the corrective feedback provided by the academic teacher on the results of the verification of learning outcomes [d01] Consulting the results of the verification of learning outcomes
reading through the academic teacher’s comments, assessments and opinions on the implementation of the task aimed at checking the level of the achieved learning outcomes
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)