Università Roma Tre

Statistical Analysis in Biology and Ecology – Descriptive, inferential and predictive statistics – Measures of dispersion – Mean and median – Probability distributions – Formulating and testing hypotheses – Null hypothesis – One-tailed and two-tailed tests – Parametric and non-parametric tests – t test and non-parametric analogues – Analysis of frequency data- Analysis of variance (ANOVA) – Analysis of covariance – Statistical power and robustness – Correlations and regressions – Generalized linear models – Advanced statistical models in ecology (mixed effects models, model selection, testing model performance) – Multivariate analysis (PCA, discriminant analysis) – Advanced methods (given sufficient time: Matrix analysis and Mantel tests, Monte Carlo methods) – Introduction to the statistical software R – Types of variables – Graphic functions – Performing analyses in R – Advanced methods in R (given sufficient time: for loops, writing functions, randomizations).

Materials, PDFs of lecture slides and scripts are made available during the course

Suggested textbooks:
Crawley, M.J. (2007) The R Book. Wiley.
Gotelli & Allison. A Primer in Ecological Statistics, Sinauer Ass. Inc.


Software:
R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.

Office hours by appointment via email: marta.carboni@uniroma3.it