Ateneo - UPO

Introduction to statistical analysis: from the basic notions to the main univariate and multivariate statistical techniques.
Introduction to cartographic analysis in R for obtaining thematic maps

All the materials (presentations and R scripts) will be provided to students during the lessons. For further information here are the suggested textbooks:
1) Statistica per ornitologi e naturalisti (2002). Authors: Flower, Cohen. Ed: Franco Muzzio (Collana Scienze Naturali)
2) Borcard, D., Gillet, F., & Legendre, P. (2011). Numerical ecology with R (Vol. 2, p. 688). New York: springer.

The course aims at providing a basic knowledge on the possible applications and functions of the software R in terms of statistical analysis and spatial analysis (cartographique)

No specific required background knowledge is needed

Lessons in classroom with the laptop. R scripts with the codes for the analyses will be provided to students. In-classroom exercises and taks are planned.

Students are encouraged to use their own laptop during the lessons.

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-students-physical-or-learning-disabilities.
Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

The examination includes two tasks:
1) a written examination (multiple choice test). This account for 50% of the final grade
2) an oral examination. Each candidate should present and discuss the results and even the R script used for achiving the goal(s) of an assigned exercise. This account for 50% of the final grade

Introduction to statistical analysis and basic concepts, with a special focus on ecological data: types of data, basic statistics and probability
Introduction to R (and RStudio) and basic notions: create and visualize objects in R, import databases in R
Data manipolation in R: data selection, modify a dataset, merge two datasets
Data exploration
Univariate statistical analyses: Student test, Mann-Whitney U test, Wilcoxon, ANOVA, Kruskal-Wallis. Pearson and Spearman correlation indices.
Univariate statistical analyses: linear regression models and model selection
Multivariate statistical analyses: Principal Component Analyis, constrained e unconstrained techniques, multivariate analyses for ecological data
Introduction to cartographic analysis in R: types of spatial data, thematic maps

To learn the basic theoretical notions of the main statistical analysis techniques and their range of applicability with respect to the aim of the study and the type of data. To learn how to perform by yourself statistical analyses by using the statistical software R. To lean how to create thematic maps in R.