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  3. Licenciatura in Sociology (After Work)
  4. Multivariate Data Analysis

Multivariate Data Analysis

Objectives

a) Understanding of how to use systematic, statistical and computer processing of data in relation to the general research strategy; b) Knowledge of and ability to apply mediator operations between the research dossier and analytical protocol; c) Ability to define the technical specifications for data analysis; d) Knowledge of and ability to use the principal statistical solutions for purpose of multivariate data analysis in Sociology; e) Knowledge and ability to use the analyses and measures of association for purposes of multivariate processing; f) nderstanding of modes of integration in analytical protocols, factor analysis (simple and multiple) and post factor analysis techniques; g) Understanding of algorithms of simple and multiple multivariate analyses; h) Ability to use the main computer programmes for statistical processing on the market; i) Ability to communicate the results of multivariate statistical analyses and their interpretation in a rigorous and significant manner.

General characterization

Code

711081059

Credits

6.0

Responsible teacher

Ana Lúcia Albano Teixeira

Hours

Weekly - 4

Total - 168

Teaching language

Portuguese

Prerequisites

Available soon

Bibliography

Benzécri, J. P. (1973). L´analyse des données: l´analyse des correspondances. Dunod. Benzécri, J.-P., et al. (1982). L’analyse des données: 2 l’analyse des correspondances. Dunod. Benzécri, J.-P., et al. (1984). L’analyse des données: 1 la taxinomie. Dunod. Carvalho, H. (2008). Análise multivariada de dados qualitativos. Utilização da ACM com o SPSS. Sílabo. Ghiglione, R., & Matalon, B. (1992). O Inquérito. Teoria e prática. Celta. Guimarães, R. C., & Cabral, J. S. (1997). Estatística. Lisboa: McGraw Hill. Hill, M. M., & Hill, A. (2000). Investigação por questionário. Sílabo. Marôco, J. (2010). Análise estatística com o PASW Statistics. Report Number. Pestana, M. H., & Gageiro, J. N. (2000). Análise de dados para ciências sociais. A complementaridade do SPSS. Sílabo.

Teaching method

Lectures presenting systematized and structured knowledge of both tehoretical and technical nature;
Exercises carried out in practical classes and as homework.

Evaluation method

Método de avaliação - two written tests (45% each)(90%), Continuous evaluation of exercises carried out in class (10%)

Subject matter

1. Methodological and statistical assumptions for multivariate data analysis 2. Multiple Correspondences Analysis 3. Principal Component Analysis 4. Classification Analysis - Cluster Analysis 5. Introduction to Linear Regression Analysis - Simple Linear Regression Analysis