Dettagli sull'Insegnamento per l'A.A. 2019/2020

Prerequisiti

It is required a basic knowledge in • Basic Mathematics • Linear Algebra • Calculus Also, a basic knowledge of Probability is strongly advised.

Obiettivi

The students, by attending this course, should acquire a basic knowledge in statistics, to be able to understand the basic theoretical tools in data management. Moreover, they should be able to solve simple theoretical statistical problems, involving the use of probability and statistics. They should also be able to tackle real simple statistical problems and employ the correct theoretical and software tools to solve them. Finally, the students should acquire sufficient skills to proceed towards a more advanced course in statistics, econometrics or in statistical learning.

Sillabo

• Using Statistics to summarize data sets: representation of datasets, sample mean, variance, median, covariance and correlation.
• Review of fundamentals of probability: combinatorics, uniform probability spaces, independence and conditioning, main discrete and continuous random variables, marginal and joint distributions, Mean, variance, moments, covariance and correlation index. The Gaussian densities, the Law of Large Numbers, the Central Limit Theorem.
• Distribution of sampling statistics, estimators, confidence intervals.
• Linear regression: univariate and multivariate.
• Principal component analysis
• RE software to calculate statistics figures

Descrittori di Dublino

Alla fine del corso, lo studente dovrebbe

Testi di riferimento

• S. M. Ross, Introductory Statistics , Academic Press.    
• R. A. Johnson, D.W: Wichern , Applied Multivariate Statistical Analysis (6th Edition) , Pearson.    

Modalità d'esame

Written exam, with possible development of a small project with the aid of a statistical software.

Aggiornamenti alla pagina del corso

• A.A. 2017/2018
• A.A. 2018/2019
• A.A. 2019/2020