88263 - STATISTICAL ANALYSIS AND MODELLING

Anno Accademico 2019/2020

  • Docente: Emanuel Guariglia
  • 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

1. Remarks of probability theory
Approaches to Probability Theory. Axiomatic approach to probability. Sets and Events. Conditional probability. Independent events. Total probability theorem. Random variables. Mean, quantiles and variance. Discrete and Continuous Uniform distribution. Binomial distribution. Gaussian distribution. Independent variables. Sums of random variables. Central limit theorem and related results. Chi-squared and t distributions.


2. Multivariate statistics

Introduction to multivariate data analysis. Linear algebra and Euclidean geometry. Descriptive statistics for data matrices. Mean vector. Covariance matrix. Distance matrix.Principal component analysis. Cluster analysis. Correspondence Analysis, Multidimensional scaling, Discriminant analysis. Linear and multiple regression.


3. Real world applications

Applications of the main statistical models in ecological, economical and social data. Further applications in biology and natural science. 

A brief introduction to statistical software: R and Wolfram Mathematica.

Testi/Bibliografia

1. S.M. Ross, Introduction to probability and statistics for engineers and scientists, Academic Press, 2014.

2. A. Papoulis, S.U. Pillai, Probability, random variables and stochastic processes, McGraw-Hill, 2015.

Moreover, lecture notes are available on IOL.

Metodi didattici

Class lectures.

Modalità di verifica e valutazione dell'apprendimento

Prerequisites

Calculus and Linear Algebra.

Format

Oral examination.

Strumenti a supporto della didattica

Teaching material (lecture notes, exercises, etc.) and further information about the course will be made available at the beginning of the course.

Orario di ricevimento

Consulta il sito web di Emanuel Guariglia