Classes (Academic Year 2008/2009):

Applied Statistics
10 Credits - Master Level
Lecturer: G. Porzio

Part 1 – Statistical Methods for Economics and Finance

Course topics: Model building in regression, Nonparametric and parametric regression, Model Diagnostics, Case Diagnostics (Outliers and Influential cases), Variables Selection, Basic Logit and Probit Regression.

Textbook: Cook R. D., Weisberg S., “Applied regression including computing and graphics”, Wiley, 1999.

Part 2 – Categorical Data Analysis and Structural Equation Models

Course Topics: Categorical response, contingency tables, logit and probit models, extreme value models, generalized linear models, log-linear models. Model notation, Covariances and Path Analysis, Causality and Causal Models, Structural Equation Models with Observed Variables, The Consequences of Measurement Error, Measurement Models: the Relation between Latent and Observed Variables, Confirmatory Factor Analysis, The General Model and Extensions

Agresti A., "Categorical Data Analysis", Wiley, New York, 2002
K.A. Bollen, Structural Equations with Latent Variables, Wiley, 1989
R.B. Kline, Principles and Practice of Structural Equation Modeling, 2nd Edition, The Guilford Press, 2005
Reader with selected articles.

5 Credits – Master Level
Lecturer: G. Zezza

Course topics: Economic cycle analysis, Trends and cycles, Transformations, Integration analysis, Forecasting (financial market analysis), Instrumental variables, Basics of c o-integration.

Marno Verbeek (2004): A course in econometrics, 2nd edition, Wiley.

Elements of Statistical Inference
(Elementi di Inferenza Statistica)
5 Credits – Master Level

Lecturer: D. Vistocco

Course topics: Univariate and multivariate random variables, Likelihood function, Maximum likelihood estimate, Likelihood ratio test, Wald test, Score test, Confidence intervals based on the likelihood, Likelihood in simple regression model.

Textbook: Azzalini A., “Statistical inference”, Chapman & Hall, 1996.

Evaluation methods through social indicators
(Metodi di valutazione attraverso l’uso di indicatori sociali)
5 Credits – Undergraduate Level

Lecturer: L. Natale

Course topics: Methods for the development of social indicators, Social behaviour models, synthesis of social indicators, human development indicators, household budget indicators.

Exploratory data analysis
(Analisi dei dati)
5 Credits – Undergraduate/Master Level

Lecturer: S. Balzano

Course topics: Basics of Linear Algebra, Dimension Reduction Techniques: Principal Component Analysis, Simple and Multiple Correspondence Analysis. Unsupervised Classification (hierarchical, non-hierarchical and mixed).
Case studies analysis using SPAD.

Textbook: Lebart L., Morineau A., Warwick K., “Multivariate Descriptive Statistical Analysis”, Wiley, 1984.

Introductory Statistics
(Statistica I parte)

5 Credits - Undergraduate Level

Lecturers: M. Furno, G. Porzio

Course topics: Univariate and bivariate descriptive statistics: measures of location, variability, mutual variability and shape. Introduction to algebra of events, probability and random variables. Selected computer-assisted lectures using Excel (by R. Salvatore).

Levine, Krehbiel, Berenson, “Business Statistics: A First Course”, Prentice Hall.
Wonnacott, Wonnacott, “Introductory Statistics”, Whiley.

Intermediate Statistics
(Statistica II parte)

5 Credits - Undergraduate Level/Master Level

Lecturer: M. Furno, D. Vistocco

Course topics: Algebra of events, Probability, Random variables, Principal univariate distributions and density functions, Inference, Estimation methods, Sampling distribution, Hypothesis testing, Confidence intervals, Simple linear regression model: point estimates and testing.

Textbook: Levine, Krehbiel, Berenson, “Business Statistics: A First Course”, Prentice Hall.

Wonnacott, Wonnacott, “Introductory Statistics”, Whiley.

Multiple Linear Regression
(Analisi statistica multivariata)
5 Credits – Master Level

Lecturer: M. Furno

Course topics: Multiple linear regression, OLS estimator and its asymptotic properties, OLS based inference, Chow test for the stability of the coefficients, Forecasts, Diagnostic measures, Robust regression estimators, Quantile regression estimator, Removing the assumptions (heteroskedasticity, autocorrelation). Empirical applications and examples are implemented with Stata.

Maddala, “Introduction to Econometrics”, Macmillan.
Pindyck, Rubinfeld “Econometric Models and Economic Forecasts”, McGraw Hill.

Sampling and Survey methods
(Indagini campionarie e sondaggi demoscopici)

5 Credits – Undergraduate Level

Lecturer: L. Natale

Course topics: Sampling methods, Survey design, Panel data.

Statistical Methods for Marketing Research
(Analisi di mercato)

5 Credits - Master Level

Lecturer: R. Salvatore

Course topics: Survey sampling: sampling from finite population, survey plans and methods for marketing research, domain estimation, optimum allocation, questionnaires. Consumer behavior: marketing models, customer satisfaction indexes. Market segmentation, prediction of behavior and marketing analysis.

Cochran W. G., "Sampling techniques", Wiley, New York, 1977
Sudman S., "Marketing research: a problem solving approach", McGraw-Hill, 1998