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STATISTICS II
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STATISTIC II
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Academic year 2014/2015
- Course ID
- SEM0022
- Teaching staff
- Antonio Canale (Titolare del corso)
Pierpaolo De Blasi (Titolare del corso) - Degree course
- Insurance and Statistics
- Year
- 1° anno
- Teaching period
- Secondo semestre
- Type
- Affine o integrativo
- Credits/Recognition
- 6
- Course disciplinary sector (SSD)
- SECS-S/01 - statistica
- Delivery
- Tradizionale
- Language
- Inglese
- Attendance
- Facoltativa
- Type of examination
- Scritto
- Prerequisites
- The knowledge of the topics of a basic course of Statistics and Probability Calculus is required.The knowledge of the topics of a basic course of Statistics and Probability Calculus is required.
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Sommario del corso
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Course objectives
The course aims at introducing the bases of multivariate analysis and nonlinear statistical modeling. Main topics are principal component analysis, factor analysis, cluster analysis and generalize linear models (GLM) with particular emphasis on logistic regression and log-linear models.The course aims at introducing the bases of multivariate analysis and nonlinear statistical modeling. Main topics are principal component analysis, factor analysis, cluster analysis and generalize linear models (GLM) with particular emphasis on logistic regression and log-linear models.- Oggetto:
Results of learning outcomes
This course will provide students with the fundament of statistical modelling. Students will learn how to take real world phenomena with suitable statistical tools and models. Estimation and testing techniques will be introduced and particular emphasis will be devoted to the interpretation of the output of the analysis, in order to transform empirical evidence into knowledge. The course will give to students the suitable basis for further studies and applications of Statistics.This course will provide students with the fundament of statistical modelling. Students will learn how to take real world phenomena with suitable statistical tools and models. Estimation and testing techniques will be introduced and particular emphasis will be devoted to the interpretation of the output of the analysis, in order to transform empirical evidence into knowledge. The course will give to students the suitable basis for further studies and applications of Statistics.- Oggetto:
Learning assessment methods
Esame solo scritto (durata h.: 3*). *Nota: per durata si intende l¿utilizzo totale dell¿aula
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Program
Multivariate analysis:Principal Component Analysis
Factor Analysis
Cluster AnalysisNonlinear Statistical Models:
Review of the linear model and maximum likelihood estimation
Generalize linear models (GLM)
Inference in GLM
Goodness of fit: deviance and residual analysis
Typical problems: logistic regression, Poisson regression and log-linear modelsMultivariate analysis:Principal Component Analysis
Factor Analysis
Cluster AnalysisNonlinear Statistical Models:
Review of the linear model and maximum likelihood estimation
Generalize linear models (GLM)
Inference in GLM
Goodness of fit: deviance and residual analysis
Typical problems: logistic regression, Poisson regression and log-linear modelsSuggested readings and bibliography
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- Azzalini, A. (1996). Statistical Inference Based on the likelihood, Chapman and Hall
Rencher A.C. (2012). Methods of Multivariate Analysis, 3rd ed. Wiley
Afifi A. and Clark V.A. (1996). Computer-aided Multivariate Analysis,
3rd ed. Chapman & HallAzzalini, A. (1996). Statistical Inference Based on the likelihood, Chapman and Hall
Rencher A.C. (2012). Methods of Multivariate Analysis, 3rd ed. Wiley
Afifi A. and Clark V.A. (1996). Computer-aided Multivariate Analysis,
3rd ed. Chapman & Hall - Oggetto:
Class schedule
Giorni Ore Aula Lunedì 14:00 - 16:00 Aula 13 Facoltà di Economia Mercoledì 14:00 - 16:00 Aula 31 Facoltà di Economia Lezioni: dal 16/02/2015 al 16/05/2015 - Oggetto:
Note
Il Corso di Studio in senso proprio è quello visualizzato all’atto dell’accesso su Campusnet. Nella videata dell’insegnamento, è indicato impropriamente come “Corso di Studio” il/i percorso/i del Corso di Laurea in cui l’insegnamento stesso è inserito.
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