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