Advanced Data Analysis

Code:

MAF012

Acronym:

ADA

Instance: 2022/2023 - 2S

Active?	Yes
Responsible unit:	Department of Sociology
Course/CS Responsible:	Masters in African Studies

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MAF	1	MAF Study Plan	1	-	6	54	162

Teaching language

Suitable for English-speaking students

Objectives

The curricular unit (CU) is divided into two interdependent parts, with autonomous program content, working on their complementarities: in the advanced quantitative methods (point 1) the objective is to explore the procedures of multivariate statistical analysis in the scope of the production of sociological knowledge and the training for the critical evaluation of its potentialities and limitations; in advanced qualitative methods (point 2) we have as objective, besides the understanding of the theoretical-epistemological and methodological foundations of the qualitative research, the knowledge and respective operationalization of some procedures of collection, treatment and analysis of qualitative data. The complementarity present in the program contents of the CU culminates with a critical reflection (point 3) on the synergies between quantitative methods and qualitative methods.

Learning outcomes and competences

1. Sound domain of the epistemological, methodological and theoretical quantitative and qualitative research procedures;

2. Ability to build and apply techniques for the collection and processing of qualitative and quantitative information;

3. Ability to search, select and process information.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Not applicable.

Program

I. Advanced Quantitative Methods: Multivariate Models and the Causal Approach in Sociology

1. Multiple linear regression model

2. Binary Logistic Regression Model

3. Models for latent structures: factorial design

4. Scale reliability analysis

5. Analysis of hierarchical clusters

III. Advanced qualitative methods: epistemological, theoretical and methodological approach

1. Qualitative research strategy: the construction of inductive knowledge

2. Qualitative sampling

3. Qualitative interviews

4. Content analysis

5. The use of qualitative data analysis programs: challenges and limitations

6. Quality and validity criteria in qualitative research

III. Qualitative and quantitative methods: proposal of articulation

 

Mandatory literature

Albarello, Luc et al. (Ed.) ; Práticas e métodos de investigação em ciências sociais, Gradiva, 1997
Arminger, Gerhard 340; Handbook of statistical modeling for the social and behavioral sciences. ISBN: 0-306-44805-X
Holliday, Adrian ; Doing and writing qualitative research, Sage, 2002
James A. Holstein; Inside interviewing. ISBN: 0-7619-2851-0
Norman Denzin & Yvona Lincoln; Strategies of qualitative inquiry, Sage, 1998
M. H. Pestana & J. Gageiro; Análise de dados para as Ciências Sociais - a complementaridade do SPSS, Edições Sílabo, 2000
Reis, E. ; Estatística multivariada aplicada, Sílabo, 2001
Uwe Flick; Métodos qualitativos na investigação científica, Monitor - Projectos e edições, 2002

Complementary Bibliography

Brian Roberts; Biographical research, Open University Press, 2002
Daniel Bertaux; Les récits de vie. Perspective Ethnosociologique, Nathan, 1997
David Silverman; Interpreting qualitative data: methods for analysing talk, text and interaction, Sage, 1993
Elizabeth Reis; Estatística multivariada aplicada, Edições Sílabo, 1998
Gilles Billotte; Analyse d.un récit de vie. ISBN: 2-13-055358-3
Hubert Blalock; Social Statistics, McGraw-Hill, 1985
Jaber F. Gubrium; Postmodern interviewing. ISBN: 0-7619-2850-2
M. Bauer; George Gaskell; Qualitative Researching with text, image and sound. A pratical handbook for social research, Sage, 2000
P. Vicente & E. Reis & J. Ferrão; Sondagens: a amostragem como factor decisivo de qualidade, Edições Sílabo, 1996
Pierre Bourdieu; L'ilusion biographique in Actes de Recherche en Sciences Sociales, nº 62/63, pp.69-72
Robert Atkinson; The life story interview, Thousand Oaks, 1998
Tom Richards & Lyn Richards; Using computers in qualitative research in Denzin & Lincoln (eds.) Collecting and Interpreting Qualitative Materials, pp.211-245, Sage, 1998
Uwe Flick; An introduction to qualitative research, Sage, 1998

Comments from the literature

Students will have access to materials for the course in the e-learning platform.

Teaching methods and learning activities

The work is organized around lectures of a more expository nature, of a theoretical-practical nature where theoretical and epistemological knowledge of both approaches are transmitted. TP classes also provide for resolution essentially technical exercises and practical work, and even experimental in some moments, in sessions that take place in a computer lab. In turn, the didactic-pedagogical methodology of the qualitative module is based on the operationalization of some procedures for collecting, processing and analyzing qualitative data. It is also a teaching-learning methodology focused on problems and application exercises, where theory and practice are dynamized in the field work.

The curricular unit also integrates distance learning tools. For this purpose, the Moodle-UP tool is used.

Software

N vivo
SPSS 22.0

keywords

Social sciences > Sociology > Socio-economic research

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Teste	50,00
Trabalho prático ou de projeto	50,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	50,00
Frequência das aulas	39,00
Trabalho de investigação	40,00
Trabalho laboratorial	33,00
Total:	162,00

Eligibility for exams

All evaluation elements are mandatory, but tests can be carried out at the time of appeal once the student has obtained a grade in the essays (both quantitative and qualitative).

Calculation formula of final grade

The evaluation focuses on the contents worked in the quantitative and qualitative component, each of which with a weight of 50% in the final classification of the course.

For each component there are 2 types of assessment elements with the following weights in the final mark.

The quantitative component (50%) is evaluated by:

-a practical test on quantitative methodologies - 25% of final classification

- a quantitative data analysis report - 25% of the final classification

The qualitative component (50%) is evaluated by:

- a practical test at the end of the qualitative module - 25% of the final classification

- a qualitative data analysis report - 25% of the final classification

Approval in the course unit has as a condition that the final classification obtained in each of the components, quantitative and qualitative, is equal to or higher than 9.5 points. The partial results of the evaluation elements defined for each of the components, quantitative and qualitative, must be equal to or greater than 8 values.

The appeal period concerns only the practical tests of the quantitative and qualitative components. Data analysis reports, quantitative or qualitative, are not subject to appeal. Submitting to an appeal test can occur either to only one of the components or to both, being in any case conditioned on obtaining a positive result in the data analysis reports.

Examinations or Special Assignments

Not applicable.

Internship work/project

Not applicable.

Classification improvement

The improvement of the classification only applies to the test about the quantitative and qualitative methodologies.

Observations

On the page of the UC, in the Moddle-UP system, all materials related to the lectures will be deposited as well as all the interactive exercises and other support materials considered relevant.