Richiami di probabilità ed inferenza statistica; Il software R; Controllo della qualità e carte di controllo; Controllo statistico della qualità con R; I numeri indici
1. Richiami di probabilità ed inferenza statistica: variabili casuali discrete e continue, valori medi, variabilità, teoria degli stimatori, intervalli di confidenza
2. Il software R: introduzione, principali funzioni statistiche, uso pacchetti specifici.
3. Controllo della qualità: la qualità nell’ambiente produttivo, il controllo statistico di processo, le carte di controllo per variabili ed attributi, carte CUSUM, carta maschera a V, carta EWMA
4. Controllo statistico della qualità con R
5. I numeri indici: a base fissa, a base mobile, indici compositi, esempi pratici.
Testi in inglese
Introduction to probability and statistical inference; Software R; Control quality and control charts; Statistical control quality with the software R; Index numbers.
MONTGOMERY D.C. (2006). Statistical quality control, 2a ed. McGraw Hill (ch.1; ch. 2 pg. 39-65, 76-80; ch. 3 pg. 81-108; ch 4; ch. 5; ch. 6; ch. 8 pg. 329-354).
The aim of the course is providing the appropriate statistical tools to carry out economic analyzes to support the companies, with particular attention to the quality control aspects. In addition, students will learn the basics of the open source statistical package R, useful for processing empirical analysis in the economic and business domain.
In particular, these objectives can be associated with the following expected learning outcomes:
a) At the end of the course students will learn the basic statistical instruments necessary to analyze economic and business data. Specifically, issues related to statistical inference, quality control and the construction of economic indicators will be proposed during the course. The presence of exercises and case studies will allow to give an empirical statistical view of real cases in business analysis. The topics will all be supported by applications with the software R
b) The aim of the course is to develop critical skills in empirical analysis, through the application of statistical tools on real studies of business phenomena. The use of the software R will allow the student to extend and adapt his knowledge in different analytical and empirical contexts.
Prerequisiti: Knowledge of Basic Statistics is required
Metodi didattici: Lectures, exercises and R practice examples
Modalità di verifica dell’apprendimento:
a) Knowledge and understanding: the verification of the learning outcomes will be carried out through a written exam. This will cover the whole program of the course, both in its theoretical and practical aspects, also through empirical examples of the software R. The oral examination can be requested by the teacher and/or by the student.
b) Applying knowledge and understanding: The exam will verify the student's ability to solve and deal with the analysis of real data, both in terms of calculation and R processing.
1. Introduction to probability and statistical inference: discrete and continuous random variables, mean values, variability, estimator theory, interval estimation
2. Software R: introduction, fundamental statistical function, use of specific packages
3. Control quality: process control quality, control charts for variables and attributes, CUSUM charts, V and EWMA charts
4. Statistical Control quality with the software R
5. Index numbers: fixed base index, mobile base index, composite indexes, and practical examples.