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Análise de Dados Multivariados

Código 15616
Ano 1
Semestre S1
Créditos ECTS 8
Carga Horária TP(60H)
Área Científica Matemática
Learning outcomes 1. Understand and differentiate the most common methods for multivariate data analysis.
2. Identify and adjust the appropriate model to a multivariate data set.
3. Interpret and communicate the results from a multivariate statistical analysis.
4. Know how to use a statistical software in the analysis of multivariate data.
Syllabus 1. Multiple Regression Models:
1.1. Linear Regression: model; parameter estimation (least squares method); inferences about the model; validation of model assumptions.
1.2 Logistic Regression: model adjustment (maximum likelihood method); significance and model quality.
2. Principal Components Analysis: model; estimation of principal components; rotation and interpretation of the main components.
3. Factor Analysis: model; estimation of common and specific factors; factor rotation; oblique rotation methods; factor scores.
4. Cluster Analysis: probabilistic formulation; hierarchical and non-hierarchical methods; cluster number choice.
5. Discriminant Analysis: selection of discriminant variables; estimation of discriminant functions; classification trees.
Main Bibliography Principal:
- Hardle, W.K., Simar, L. (2019) Applied Multivariate Statistical Analysis (5th ed.), Springer
- Johnson, R.A. e Wichern, D.W. (2007) Applied Multivariate Statistical Analysis (6th ed.), Prentice-Hall
- Mardia, K.V., Kent, J.T., Bibby, J.M. (1979) Multivariate Analysis, Academic Press
- Johnson D. E. (1998) Applied Multivariate Methods for Data Analysts, Duxbury Press & Brooks/Cole

Complementar:
- Everitt, B., Hothorn, T. (2011) An Introduction to Applied Multivariate Analysis with R, Springer (Use R! Series)
- Denis, D. (2020) Univariate, Bivariate, and Multivariate Statistics using R, Quantitative tools for data analysis and data science, John Wiley and Sons Ltd
Language Portuguese. Tutorial support is available in English.

Regente

Imagem d@ Jorge Gama [Ficheiro Local]
 Jorge Gama

Curso

Matemática e Aplicações
Data da última atualização: 2024-09-19
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