- Docente: Cinzia Franceschini
- Crediti formativi: 6
- SSD: SECS-S/01
- Lingua di insegnamento: Inglese
- Modalità didattica: Convenzionale - Lezioni in presenza
- Campus: Bologna
- Corso: Laurea Magistrale in Scienze e gestione della natura (cod. 9257)
Conoscenze e abilità da conseguire
At the end of the course, the student learn major statistical methods to deal with ecological, economical and social data, both using univariate and multivariate approaches. The student will have the capacity to deal with the practical applications of several statisical methods to real world case and data.
Contenuti
Learning outcomes
At the end of the course, the student will have a good knowledge of basic and advanced multivariate statistical techniques useful to conduct statistical analysis on real dataset. The course blends theory and practice for a better understanding of the subject.
Univariate Statistics:
Descriptive statistics and introduction to statistical distributions
Location measures : mean, median, mode
Graphical representation: frequency distribution, bar graphs, histograms
Measures of scatter: range, inter-quartile range, variance
Bivariate Statistics:
Two-way tables: joint, marginal and conditional distributions
Association: independence, chi-square test
Concordance: covariance, correlation
Multivariate Statistics:
Data matrix
Mean vector
Covariance matrix
Distance Matrix
A brief introduction to the following multivariate statistical techniques: Principal Components, Cluster Analysis.
Regression:
Simple Linear Regressione
Multivariate Linear Regression
Concentration Matrix
Partial Correlation
Distributions:
Normal Distribution
Sample Mean
Statistical Hypotheses
ANOVA
Testi/Bibliografia
Izenman, A. J. (2008). Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning, Springer.
Thomas H. Wonnacott, Ronald J. Wonnacott , Introductory Statistics, 5th Edition, Wiley.
Peter Dalgaard. Introductory Statistics with R. Springer, New York, 2002.
John Verzani. Using R for Intoductory Statistics. Chapman & Hall/CRC, Boca Raton, FL, 2005.
Slides of the course.
Metodi didattici
Frontal Lectures
Modalità di verifica e valutazione dell'apprendimento
Written exam with TRUE/FALSE questions and exercises. (If the exam will be in presence).
Oral exam (If it , due to COVID, will be online)
Strumenti a supporto della didattica
Slides
Orario di ricevimento
Consulta il sito web di Cinzia Franceschini