It is intended with this unit, that students acquire familiarity with:
• The main scientific and epistemological debates about the concepts of method and methods applicable to large data sets.
• Ability to critically read studies relating them to particular methodological perspectives.
• Understand the logic of the possible relationship between different types of methods.
• Develop research designs according to scientific methodology.
• Formulate research hypotheses and operationalize concepts.
• Critically explain the concept of variable, dependent and independent variables and the importance of the scalar level.
• Notion of the power of the statistics, their relationship with the scales of the variables and conditions of use of scales for the application of statistical tests.
• Know the main statistical resources for the constitution of representative samples, hypothesis tests, collection and analysis of standardized data.
• Understand the distinction between general, strong and significant causal effects.
1. Main scientific and epistemological debates about method concepts and methods applicable to large data sets.
2. Research organization
2.1. Research project
2.2. Research Designs
2.3. The validity of the research design
3. Research design according to scientific methodology.
3.1. Formulate research hypotheses, operationalize concepts.
3.2. The concept of variable, dependent and independent variables and importance of the scalar level (review).
3.3. Observation instruments: concepts of analysis field and representative sample, Questionnaire survey.
4.1. The Normal curve, Data distributions, characteristics of the Normal curve
4.2. Calculation of the size of a representative sample
5. Statistical resources for standardized data analysis.
5.1. Understand the distinction between general, strong and significant causal effects
5.2. Hypothesis tests based on differences between population means: t Test, Z Test
5.3. Concept of power of a test.
5.4. Types of errors (I and II) and consequences of their occurrence
FERNANDES, F. (1980). Fundamentos empíricos da explicação sociológica. S. Paulo: TAQ.
QUIVY, R. e CAMPENHOUDT, L. (1998). Manual de investigação em ciências sociais. Lisboa: Gradiva.
D’ANCONA, M. (2001).Metodología cuantitativa estratégias e técnicas de investigação social. Madrid: Editorial Síntesis S. A.
PORTA, D. e KEATING, M. (2008). Approaches and Methodology in the social sciences a pluralist perspective. Cambridge: University Press.
LEVIN, J. (1987). Estatística aplicada a ciências sociais. S. Paulo: Editora Habra Lda.
SPIEGEL, M. (1984). Estatística. S. Paulo: McGrow-Hill do Brasil.
PEDROSA, A. e GAMA, S. (2004). Introdução computacional áprobabilidade e estatística. Porto: Porto Editora.
WELKOWITZ, EWEN and COHEN. (1991) Statistics for the behaviorial sciences. Orlando:HBJ Publishers.
Continuous assessment is privileged: 2 or 3 digital written documents (e-folios) during the semester (40%) and a
presence-based final exam (p-folio) in the end of the semester (60%). In due time, students can alternatively choose to perform one
final presence-based exam (100%).
Universidade Aberta has SPSS academic licenses for personal computers free for students. The instructions of the procedures relating to requests for spss, are in http://spss.si.uab.pt