Análise de Dados Multivariada

Univariate and bivariate descriptive statistics.

As there is no teaching component in the current school year, there is no recourse to any teaching method.

The main goal of this course is to provide students with a set of techniques for data analysis when they involve more than two variables. In particular, it is intended that students deepen and broaden the knowledge they need to analyze data, understand the aim of the covered techniques, apply them using an appropriate software (SPSS) and correctly interpret the results.

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: definition, 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.

• - Trabalho prático 1 - 25.0%
• - Trabalho prático 2 - 25.0%
• - Teste - 50.0%

• - Trabalho prático 1 - 25.0%
• - Teste - 50.0%
• - Trabalho prático 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. (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.ª ed.).  Edições Sílabo.

Wooldridge, J.M. (2020). Introductory Econometrics: A Modern Approach (7.ª ed.). Cengage Learning.