Base Knowledge
Preliminary data analysis and graphical representation.
Teaching Methodologies
The theoretical exposition of the subjects is accompanied by the presentation of practical examples, supported by computer tools (Microsoft Excel and SPSS) and the resolution of exemplifying exercises transmitting the concepts of Statistics applied to Social Sciences.
Learning Results
1) Identify and collect qualitative/quantitative data relevant to the case study.
2) Select appropriate statistical analysis techniques to describe the available data.
3) Numerically and graphically organize the results of the use of different statistical methodologies.
4) Correctly interpret numerical and graphic results.
5) Use data analysis programs (Microsoft Excel / SPSS – Statistical Package for Social Sciences).
Program
Module 1 (Weight: 50%)
1. Descriptive statistics.
2. Elementary probability theory. Discrete and continuous one-dimensional random variables. Most common theoretical distributions: discrete and continuous.
Module 2 (Weight: 50%)
3. Hypothesis tests for a population parameter.
4. Simple linear regression.
Curricular Unit Teachers
Cláudia Susana Pereira dos SantosGrading Methods
Continuous assessment:
Minimum presence - Regulamento Académico do 1º Ciclo de Estudos
Module 1 (M1) - Evaluates the learning outcomes of chapters 1 and 2. Weight: 50%.
- Written test 1 - 35%
- PC Work 1 - 15%
Module 2 (M2) - Evaluates the learning outcomes of chapters 3 and 4. Weight: 50%.
- Written test 2 - 35%
- PC Work 2 - 15%
Tests and PC works are mandatory. Minimum grade per module of 7.5 values.
Final grade = 0.50 *M1 + 0.50 * M2
To obtain approval, in continuous evaluation, the student has to meet the minimum attendance and the final grade resulting from the weighted final grade equal to or greater than 9.5 values (scale 0-20).
Assessment by exam:
Exam to assess both modules.
If the student, in the continuous assessment, has obtained a minimum grade of 7.5 in one of the modules, he/she can reuse the grade for that module. When performing proof for only one of the modules, the minimum grade of 7.5 values is maintained. Approval in the curricular unit depends on obtaining a minimum of 9.5 values in the final grade.
In the exam for grade improvement, there is no place for the reuse of grades obtained in continuous evaluation.
Internship(s)
NAO
Bibliography
Murteira, B., Ribeiro, C., Silva, J. & Pimenta, F. (2023). Introdução à Estatística. Escolar Editora. 4ª ed.
Reis, E., Melo, P., Andrade, R. & Calapez, T. (2021). Estatística Aplicada, vol. 1. Edições Sílabo. 7ª ed.
Reis, E., Melo, P., Andrade, R. & Calapez, T. (2019). Estatística Aplicada, vol. 2. Edições Sílabo. 6ª ed.
Pedrosa, A. C. & Gama, S. M. (2016). Introdução Computacional à Probabilidade e Estatística com Excel. Porto Editora. 3ª ed.
Levine, D., Stephan, D. & Szabat, K. (2016). Estatística: Teoria e Aplicações usando o Microsoft Excel em Português. LTC Editora. 7ª ed.
Maroco, J. (2021). Análise Estatística com o SPSS Statistics. Editora ReportNumber. 8ª ed.
Maroco, J. & Bispo, R. (2005). Estatística aplicada às ciências sociais e humanas. Climepsi Editores. 2ª ed.