- test offerta formativa
- Master's Degree in COASTAL AND MARINE BIOLOGY AND ECOLOGY
- MATHEMATICAL MODELLING IN ECOLOGY
MATHEMATICAL MODELLING IN ECOLOGY
- Teaching in italian
- MATHEMATICAL MODELLING IN ECOLOGY
- Teaching
- MATHEMATICAL MODELLING IN ECOLOGY
- Subject area
- SECS-S/02
- Reference degree course
- COASTAL AND MARINE BIOLOGY AND ECOLOGY
- Course type
- Master's Degree
- Credits
- 6.0
- Teaching hours
- Frontal Hours: 48.0
- Academic year
- 2022/2023
- Year taught
- 2022/2023
- Course year
- 1
- Language
- ENGLISH
- Curriculum
- Curriculum E-Biodiversity and Ecosystem Sciences
- Reference professor for teaching
- ARIMA SERENA
- Location
- Lecce
Teaching description
Basic concepts of mathematics and statistics.
The main goal of the course is to provide basic tools for analyzing ecological data with focus on probabilistic and mathematical modeling issues. In particular the course deals with:
1) Introduction to statistics and probability;
2) Association and entropy measures;
3) Probability and statistical inference for Normal and not Normal populations;
4) Linear models and non linear models.
During the course, the statistical software R will be illustrated and the students will be able to elaborate their data using it.
The course aims at providing basic methodologies for analyzing ecological data and modeling their intrinsic variability.
Slides, exercises provided on the web page. Practical exercises with the statistical software R.
Written exam with R.
1. Introduction: why analyzing data in ecology?
2. Exploratory data analysis and graphics
3. Deterministic functions for ecological modelling
4. Probability and stochastic distribution of ecological modeling
5. Stochastic simulation and power analysis
6. Statistical inference
7. Linear regression model and generalized linear models
8. Non linear models
9. Modelling variance
10. Dynamic models
During the course, the statistical software R will be illustrated and the students will be able to elaborate their data using it.
B. Bolker (2007) Ecological models and Data with R, PRINCETON UNIVERSITY PRESS.
A. Zuur, E.N. Ieno, G.M. Smith (2007) Analyzing ecological data, Springer Ed.
Interesing web book: http://web.stanford.edu/class/bios221/book/introduction.html
Semester
Second Semester (dal 06/03/2023 al 09/06/2023)
Exam type
Compulsory - Related/Supplementary
Type of assessment
Oral - Final grade
Course timetable
https://easyroom.unisalento.it/Orario