Methods and techniques of Quantitative Research


Knowledge and understanding of the principles and applications of the quantitative methods and techniques more currently used in sociological research.

Ability to choose among quantitative methods and techniques, minding the research objectives and the empirical data to be/already collected.

Ability to interpret critically the results of different methods and techniques in published sociological research.

General characterization





Responsible teacher

Ana Lúcia Albano Teixeira


Weekly - Available soon

Total - 224

Teaching language



Available soon


Carvalho, H. (2008). Análise Multivariada de Dados Qualitativos: Utilização da ACM com o SPSS. Lisboa: Sílabo.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis. Essex: Pearson.
Laureano, R. (2011). Testes de Hipóteses com o SPSS: O meu Manual de Consulta Rápida. Lisboa: Sílabo.
Marôco, J. (2014). Análise de Equações Estruturais: Fundamentos Teóricos, Software e Aplicações. Lisboa: Report Number.
Marôco, J. (2011). Análise Estatística com o SPSS Statistics. Lisboa: Report Number.
Reis, E. (2007). Estatística Descritiva. Lisboa: Sílabo.
Reis, E., Melo, P., Andrade, R., & Calapez, T. (2001). Estatística aplicada (Vol.2). Lisboa: Sílabo.
Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics. Boston: Pearson.
Vicente, P., Reis, E., & Ferrão, F. (2001). Sondagens: A Amostragem como Factor Decisivo de Qualidade. Lisboa: Sílabo.

Teaching method

Example-driven taught classes; practical exercises performed or corrected in class, including analysis and critical interpretation of published results and the discussion of hypothetical choices aiming at given research objectives.

The essay will be written on a scientific book or paper chosen by the student, which meets the following requirements:
a) it must follow quantitative methodology;
b) it must employ at least two of the techniques taught in class.
The essay shall focus on the methodological component, relating it with the scientific object.

Evaluation method

1) One 8 to 10-page written essay(60%), 2) In-class presentation and discussion of said essay (40%)

Subject matter

1. Kinds of data and measurement scales
2. Sampling
a. representativeness
b. kinds of samples
c. sampling error
3. Descriptive statistics
a. graphic representation
b. frequency and contingency tables
c. central tendency measures
d. dispersion measures
e. normal distribution
4. Chi-squared independence test (hypotheses testing)
5. Association measures
6. Correlation coefficients
7. Tests to the comparison of means: t test for independent samples
8. Variance analysis: one-factor ANOVA
9. Multiple | multilevel multiple regression
10. Multiple Correspondence Analysis (MCA)
11. Multidimensional Scaling (MDS)
12. Principal Components Analysis (PCA)
13. Structural Equations Models (SEM)


Programs where the course is taught: