At the end of this course, students will be able to apply principles of biostatistics to the biomedical research. A dialogue with statisticians and epidemiologists is encouraged when a problem requires more advanced mathematical and epidemiological details.
After this unit, students should be able to:
1. To demonstrate a basic understanding of the importance of statistics in a biomedical research.
2. To know some sampling methods, given attention to the randomness.
3. To calculate, interpret and summarise the results of the descriptive statistics and exploratory data analysis for the purpose of scientific publications
4. To perform statistical hypothesis tests (parametric and non-parametric) and confidence intervals, providing a critical interpretation of results and given a particular attention to the assumptions of each test.
5. To identify practical situations, when linear and logistic regressions may be used.

General characterization





Responsible teacher

Luzia Gonçalves


Weekly - 6

Total - 36

Teaching language



Attendance of 2/3 of classes is mandatory


• Altman, D. (2002) Poor-quality medical research. Journal of the American Medical Association, 287(21), 2765-2767.
• Armstrong, R.A., Hilton, A.C. (2010) Statistical Analysis in Microbiology: StatNotes. Wiley-Blackwell.
• Daniel, W.W. (2004) Biostatistics: a foundation for analysis in the health sciences. John Wiley and Sons, 8th Ed.
• Harrell, F. E. (2001) Regression Modeling Strategies with Applications to Linear Models, Logistic Regression, and Survival Analysis. Springer.
• Sheskin, D. J. (2007) Handbook of Parametric and Nonparametric Statistical Procedures. Chapman and Hall/CRC. 4th Ed.

Teaching method

The total contact hours (26 hrs.) will be distributed by 5 theoretical (10 hrs.), 8 theoretical and practical sessions (16 hrs.), 4 tutorial sessions (8 hrs.) and assessment (2 hrs.). In the practical sessions will be used statistical package (e.g. SPSS, EPITools and others) and other online platforms (e.g. Moodle).

Evaluation method

The final assessment will be by written exam. The exam includes different type of questions (e.g. multiple choice, true/false and essay questions).

Subject matter

I. The role of the biostatistics in biomedical research. The importance of random sampling in research. Definition and classifying variables. Cautions in data collection and data entry. Descriptive statistics and exploratory data analysis.
II. Statistical inference: parameters, statistics and sampling distributions; estimation of parameters, hypothesis testing. Concepts of parametric tests vs non-parametric tests. Confidence intervals for mean values and proportions. Alternative methods for prevalence, sensitivity, and specificity of the diagnostic tests. Sample size calculation, using confidence intervals and other situations.
III. Comparisons of populations though independent sample: assumptions of parametric test: Kolmogorov-Smirnov and Shapiro-Wilk tests and Levene test; T-Test vs Mann-Whitney; ANOVA vs Kruskall-Wallis test. Multiple comparisons. Chi-Square tests. Correlation and linear regression. Introduction to logistic regression.


Programs where the course is taught: