Cod: 21036
Department: DCET
ECTS: 6
Scientific area: Mathematics
Total working hours: 156
Total contact time: 26

In this course are tought the concepts of the design of a study, sampling techniques and data collection; development of questionnaires and statistical methods to solve problems from Health and Environment. We outline some of the most widely used techniques in the analysis of such data, which include parametric and nonparametric methods.

Data in Environment and Health
Statistical Tests
Association and Correlation
Epidemiology

By completing this curricular unit the student should be able to identify the variables of interest in a problem, define the type of study, know the basic concepts of sampling. He/her should be able to choose and apply the most appropriate statistical method for some types of biological data, health and environmental issues, using statistical software. Formulate hypotheses, select appropriate statistical tests, parametric and non parametric, for different types of data and interpret results in the context.

Types of studies and stages of a research study, planning and obtaining samples. Getting data using the questionnaire.
 • Summary of the laws of probability distribution and some of the most important theoretical results.
 • The process of Statistical Inference: Estimation of parameters. Application to biosciences.
 • Statistical tests of association between categorical variables (Fisher’s exact test, chi-square test, McNemar’s test).
 • Parametric and non parametric tests for comparing two or more independent samples (Mann-Whitney and Wilcoxon tests; ANOVA, Kruskall-Wallis and Friedman tests; L-Page and Jonckheere trend tests).
• Diagnostic tests and statistics in clinical trials. Odds Ratio.
 • Tests on the correlation coefficients. Relation with linear regression.
 • Applications of data in areas of health sciences and environmental issues.
 • Topics for using a software (Excel) in supporting the resolution of problems

Essential:
Materials will be made available at the Moodle page of the course unit.

Complementary:
Biostatistics: A Foundation for Analysis in the Health Sciences. W.W. Daniel, 9th Edition, Wiley. 2008, 2009.
Métodos de Investigação para Terapeutas Clínicos, Carolyn M. Hicks., Lusociência.
Bioestatística, Epidemiologia e Investigação - Teoria e Aplicações, A. Gouveia de Oliveira, Edições LIDEL (http://www.fca.pt/lidel_index2.html)
D. Pestana, S. Velosa  Introdução à Probabilidade e à Estatística, Vol I, Fundação Calouste Gulbenkian. 2002
Estatística Aplicada às Ciências e Tecnologias da Saúde. Gilda Cunha, M. Rosário Martins, Ricardo Sousa, Filipa F. Oliveira , Ed. Lidel. 2007.

E-learning

Continuous assessment is privileged: 2 or 3 digital written documents (e-folios) during the semester (40%) and a presence-based final exam (p-folio) in the end of the semester (60%). In due time, students can alternatively choose to perform one final presence-based exam (100%).

It is recommended that the student has previously attended and introdutory course in probability and statistics. It is recomended the course unit Introduction to Exploratory Data Analysis (LCA) ou Elements of Probability and Statistics (LMeA and LI).