Biostatistics I


The teaching of this curricular unit aims to promote the acquisition of knowledge about the basic concepts of statistics. Additionally, students will be introduced to the Statistical Package for the Social Sciences (SPSS). It is an easy-to-use statistical software that will enable students to analyse data, obtained from epidemiology studies in health sciences, by the implementation of the theoretical statistical methods learned previously. This curricular unit should promote the following skills: a) to know the basic functionalities of SPSS that will allow students: b) to do an exploratory analysis, and c) to implement the hypotheses tests after identifying which is the most appropriate.  Additionally, students should be able to read more easily a scientific paper in the field of health sciences, with a better understanding of the results.

General characterization





Responsible teacher

Prof.ª Doutora Ana Papoila


Weekly - Available soon

Total - Available soon

Teaching language





1. Altman, D. (1991). Practical statistics for medical research. First edition. Chapman & Hall, London.

2. Bland, M. (2000). An introduction to medical statistics. Third edition. Oxford University Press.

3. Daniel, W.W. (2008). Biostatistics: A foundation for analysis in the health sciences. 9th edition. John Wiley & Sons.

4. Pestana, M. H. e Gageiro, J.N. (2005). Análise de dados para ciências sociais: A complementaridade do SPSS. Edições Sílabo, Lisboa.

Teaching method

Teaching is based in the integration of: a) theoretical teaching where themes are presented by a teacher with the demand of students’ participation; b) practical teaching through the resolution of practical exercises using SPSS. Interaction between students and teachers is both at the classroom and by e-mail. Classes will take, at most, 180 minutes and will take place at a classroom with computers (1 for each student).

Evaluation method

To assess students’ performance, a formal written examination will take place where exercises must be solved using SPSS.

Subject matter

Summarizing data. Presenting data. Correlation coefficients (Pearson, Spearman and Kendall). Probability and random variables. Sampling methods. Statistical inference: estimation and hypotheses tests: basic concepts, one-sample tests, two independent samples tests (z test, t test, and Mann-Whitney test), paired samples tests (paired t-test, Wilcoxon and Sign test), more than two independent samples tests (ANOVA I and Kruskal-Wallis) and more than two related samples test (Friedman). Analysis of cross-tabulations (Chi-squared test for association and Fisher's exact test) and McNemar's test for matched samples. Interpreting results obtained by linear, logistic and Cox regression models. SPSS functionalities that will enable students to analyse the data with the statistical methodologies previously taught.


Programs where the course is taught: