Environmental Monitoring and Recovery

Lecture diary/syllabus at: http://brazil.mat.uniroma1.it/dario#didattica Introduction to dynamical systems (16 hours). Difference equations and differential equations. Qualitative analysis: equilibria and stability, bifurcations and catastrophes (ecological shift). Descriptive statistics (8 hours). Absolute and relative frequencies, graphical representations. Mean and standard deviation; medians and percentiles. Bivariate and multivariate statistics. Correlation, regression line; principal components. Regression by exponential and power laws. Review of probability (12 hours)). Independence. Bayes' formula, Law of large numbers. Random variables. The main probability distributions in modeling. Variability indices. Inferential statistics (16 hours). Estimation of the parameters of a distribution, confidence intervals. Hypothesis testing. Introduction to various statistical tests.

Basic knowledge of differential calculus, probability and elementary statistics, provided by the courses of the first year of the three-year degree.

Teacher's notes on http://brazil.mat.uniroma1.it/dario/#didattica Benedetto, Degli Esposti, Maffei: "Matematica per le scienze della vita", IV edizione G. Gaeta: "Modelli matematici in biologia", Springer Whitlock, Schluter: Analisi statistica dei dati biologici, Zanichelli 2010 Iacus, Masarotto: "Laboratorio di statistica con R"

Suggested.

The exam aims to assess learning through a written test that: - certifies the skills acquired in the exercises - certifies the acquisition of the main points of deterministic and stochastic modeling. To achieve a score of 25/30, the student must demonstrate good knowledge and proficiency in the core topics of the course. To achieve a score of 30/30 with honors, the student must demonstrate excellent proficiency and knowledge of all the topics covered in the course.

Lectures 32 hours, exercises 20 hours. Each laboratory lesson consists of a short presentation and a guided practical exercise.