Multivariate Data Analysis

Univariate and bivariate descriptive statistics.

The development of each topic in the course will have a similar structure, in particular: an introduction and characterization of the technique, with presentation and discussion of the options and outputs of SPSS using an example, and practical case resolution.

It is intended that students understand and apply the multivariate data analysis techniques covered, that they use specific software properly  and that they interpret critically the results obtained.

Introduction: Data type. Classification of multivariate techniques. Examples.

Factor Analysis: The model. Estimation of loadings. Rotation of factors. Estimation of the values of the factors. Resolution of application examples using SPSS and interpretation of the outputs.

Principal Components Analysis: The model: construction, properties, geometric meaning and interpretation. ACP on standardized data vs. non-standardized data. Resolution of application examples using SPSS and interpretation of the outputs.

Multiple Linear Regression Analysis: The model; estimation of coefficients; inference on the model. Assumptions. Methods of sequential selection of variables. Resolution of applied examples using SPSS and interpretation of results.

Cluster Analysis: Dissimilarities between individuals. Hierarchical methods and nonhierarchical methods. Resolution of application examples using SPSS and interpretation of the outputs.

Introduction to Structural Equation Models: general characterization.

• - Individual work 2 - 25.0%
• - Individual work 1 - 25.0%
• - Exam - 50.0%

• - Group Work 1 - 25.0%
• - Test - 50.0%
• - Group work 2 - 25.0%

NAO

Hair, J. F., Black, W., Babin, B., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.).Pearson.

Johnson, R. A., & Wichern, D. W. (2008). Applied Multivariate Statistical Methods (6th ed.). Pearson.

Malhotra, N. (2012). Pesquisa de Marketing: Uma Orientação Aplicada (6.ª ed.). Bookman.

Marôco, J. (2021). Análise de Equações Estruturais – Fundamentos teóricos, software & aplicações (3.ªed.). ReportNumber.

Marôco, J. (2018). Análise Estatística com o SPSS Statistics (7.ª ed.). ReportNumber.

Pestana, M. H., & Gageiro, J. N. (2014). Análise de Dados para Ciências Sociais: A complementaridade do SPSS (6.ª ed.). Edições Sílabo.

Pestana, M. H., & Gageiro, J. N. (2005). Descobrindo a Regressão – com a complementaridade do SPSS (1.ªed.).  Edições Sílabo.