Analysis of Biological and Environmental Data
A.Y. 2025/2026
Learning objectives
The course aims to provide students with the tools to: retrieve and represent biological data, such as species distribution and population abundance data, and environmental data, such as habitat, landscape and climate characteristics; evaluate relationships between environmental characteristics and biological data, through the application of the main types of statistical models
Expected learning outcomes
Students will be able to: retrieve biological data through literature searches and from the main biodiversity databases; retrieve environmental data from the main global, national, regional and local databases; use basic tools to simulate, represent and analyse biological and environmental data; use some R software functionalities to process, represent and analyse biological and environmental data.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Lesson period
Second semester
Course syllabus
The course will address the following topics: how and where to obtain biological data, climate data, land-use data and other abiotic data. It will introduce the R software, showing its use for processing, visualizing, and simulating biological and environmental data. The course will demonstrate how various parametric and non-parametric tests can be used to analyse biological and environmental characteristics such as morphology, species-habitat associations, and animal responses to environmental variation. The course will primarily focus on basic univariate tests such as: chi-square, t-test, ANOVA, correlation analysis, and linear models. Additionally, an introduction to multivariate analyses and species distribution models (SDMs) will be provided. The learning objectives will also be achieved through several computer-based exercises.
Prerequisites for admission
No mandatory prerequisites. However, it is suggested to have attended, or better, passed the following exams: "Istituzioni di matematiche e statistica", "sistemi informativi territoriali", "geografia fisica e cartografia", "zoologia", "ecologia ed etologia".
Teaching methods
Lectures will be delivered in traditional format but most of them will also include practical activities carried out by students at the computer. Slides and didactic materials will be available on myAriel.
Teaching Resources
The course will not follow a specific textbook but will be based on different sources, including:
Jim Fowler, Louis Cohen (2010) Statistica per ornitologi e naturalisti. Franco Muzzio Editore.
Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani (2021) An Introduction to Statistical Learning - with Applications in R - Second Edition. Springer. https://www.statlearning.com/
Andy Field, Jeremy Miles, Zoe Field (2012) Discovering Statistics Using R. SAGE Publications Ltd.
Jim Fowler, Louis Cohen (2010) Statistica per ornitologi e naturalisti. Franco Muzzio Editore.
Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani (2021) An Introduction to Statistical Learning - with Applications in R - Second Edition. Springer. https://www.statlearning.com/
Andy Field, Jeremy Miles, Zoe Field (2012) Discovering Statistics Using R. SAGE Publications Ltd.
Assessment methods and Criteria
The exam will be oral, in person, and will last approximately 15-30 minutes. It will consist of questions designed to assess learning and understanding of the topics covered during the course, as well as practical computer exercises. Evaluation criteria include not only the comprehension and knowledge of the material but also reasoning and problem-solving skills. The grade will be given on a 30-point scale.
BIO/05 - ZOOLOGY - University credits: 6
Lessons: 48 hours