Research Methods Lab

Recommended Prerequisites

Statistical methods and Data analysis

Teaching Methods

The teaching methodologies used in this course involve exposition of contents by the teacher, which will rely heavily on different databases so that the students can develop their knowledge in an applied way. The evaluation is done through tests and data analysis assignments.

Learning Outcomes

This course aims to complement the training of doctoral students in terms of research methodologies, giving continuity to the curricular units of statistical methods and data analysis. With the frequency of this course, students should improve their skills in the operationalization of research work, particularly in terms of data analysis, thus fostering more informed methodological choices, which will result in better research work.

Work Placement(s)

No

Syllabus

Experimental method

Multilevel modelling

Case studies

Head Lecturer(s)

Filipe Jorge Fernandes Coelho

Assessment Methods

Assessment
Periodic or by final exam as given in the course information: 100.0%

Bibliography

Alferes, V. R. (2012). Methods of randomization in experimental design (Vol. 171). Sage Publications.

Magalhães, M., & Hill, A. (2005). Investigação por questionário. Lisboa: Sílabo.

Hox, J. (2010). Multilevel Analysis: Techniques and Aplications. 2nd Ed. Lawrence Erlbaum. New Jersey.

Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s just regression. Guildford Press. New York.

Marôco, J. (2014). Análise Estatística com o SPSS Statistics. 6ª. Ed. ReportNumber. Pêro Pinheiro.