Multivariate Data Analysis

Descriptive statistics. Simple Linear Regression.

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

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 need of the covered techniques, apply them using an appropriate software (SPSS) and correctly interpret the results.

Introduction: Data type. Classification of multivariate techniques. Examples.
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.
Factor Analysis: Formulation of 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.
Cluster Analysis: dissimilarities between individuals. Hierarchical methods and nonhierarchical methods. Resolution of application examples using SPSS and interpretation of the outputs.
Multiple Linear Regression Analysis: The model. Estimation of the coefficients. Inference on the model. Assumptions. Methods for sequential selection of variables. Resolution of application examples using SPSS and interpretation of the outputs.

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

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

NAO

M. Norusis, SPSS 18.0 Guide to Data Analysis, Prentice Hall, 2010

Pestana, M. H., Gageiro, J. N., Análise de Dados para Ciências Sociais – A complementaridades do SPSS, 6ª ed, Edíções Sílabo, Lisboa 2014

Hair, J., Black, W., Babin, B., Anderson, R., e Tatham, R., Multivariate Data Analysis, Cengage Learning EMEA; 8th edition, 2018

Pestana, M. H., Gageiro, J. N., Descobrindo a Regressão – com a complementaridade do SPSS, 1ª ed, Edíções Sílabo, Lisboa 2005

Jonhson, R. A., Wichern, D. W., Applied Multivariate Statistical Methods, 6th Ed.,Prentice Hall, 2008.

Marôco, J. , Análise Estatística com o SPSS Statistics 25, 7ª ed., Report Number, 2018