Statistical methods in environmental studies
A.A. 2023/2024
Obiettivi formativi
This course provides a broad overview of statistical methods and space-time data analysis frequently used in environmental science and studies. The topics covered in this course aim to provide you with the foundation and tools needed to empirically evaluate data
Risultati apprendimento attesi
At the end of the course the student must be able to perform autonomously statistical analyses of environmental data, often having a space and/or time structure. The student must also be able to produce effective reports of the analysis.
Periodo: Secondo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Secondo semestre
Programma
* Probability and random variables.
* Statistical inference and environmental sampling.
* Bayesian models and computation.
* Regression-type models and methods: multiple regression, Poisson and logistic regression.
* Environmental monitoring and impact assessment.
* Introduction to Time series and forecasting.
* Introduction to the Analysis of spatial data: areal and point-referenced data.
* Statistical inference and environmental sampling.
* Bayesian models and computation.
* Regression-type models and methods: multiple regression, Poisson and logistic regression.
* Environmental monitoring and impact assessment.
* Introduction to Time series and forecasting.
* Introduction to the Analysis of spatial data: areal and point-referenced data.
Prerequisiti
The students should be familiar with basic concepts of matrix algebra, Calculus I and should have attended a basic course in probability and statistics.
Metodi didattici
Face-to-face lectures and practical sessions using R and RStudio (students will be required to solve problem sets in the lab or using their laptops).
Materiale di riferimento
* Manly B.F.J, 2009, Statistics for Environmental Science and Management, CRC Press.
* Qian S.S., DuFour M.R., Alameddine I., 2022, Bayesian Applications in Environmental and Ecological Studies with R and Stan. CRC Press.
* Course notes and links to online resources (course website)
* Qian S.S., DuFour M.R., Alameddine I., 2022, Bayesian Applications in Environmental and Ecological Studies with R and Stan. CRC Press.
* Course notes and links to online resources (course website)
Modalità di verifica dell’apprendimento e criteri di valutazione
The main purpose of the written exam is to assess the achievement of the learning objectives, such as the ability to select the appropriate model to answer research questions, to read the output of statistical softwares, to perfom the appropriate analysis, to use statistical models to support decision making. The exam (about 1 hour) consists of a written test with exercises composed of several open and closed questions both theoretical and/or focused on the output from the R software to be commented.
SECS-P/05 - ECONOMETRIA
SECS-S/01 - STATISTICA
SECS-S/01 - STATISTICA
Esercitazioni: 32 ore
Lezioni: 32 ore
Lezioni: 32 ore
Docente:
Stefanini Federico Mattia
Siti didattici
Docente/i
Ricevimento:
Su appuntamento Martedì e Mercoledì (email)
via Celoria 10