Biostatistics, Principles and Applications
At the end of this course the students should:
1. Explore the main sources of statistical information on health and recognize the most commonly used indicators in decision-making
2. To distinguish the various types of data, their scales of measurement and the most appropriate way to organize information in charts and graphs
3. Build and interpret frequency tables
4. Calculate and interpret descriptive statistics measurements (central tendency and dispersion)
5. Explore and synthesize data in healthcare, according to their different characteristics
6. Calculating odds for classical definition and using the axiomatic, including conditional probabilities
7. Describe dependence / independence factors, its impact and importance in the context of Health
8. Describe a random variable and understand the use of models to calculate odds
9. To characterize the probability distributions Binomial, Poisson and Normal and calculate probabilities from these models
Isabel Cristina Maciel Natário, Maria do Rosário Fraga de Oliveira Martins Sentieiro
Weekly - Available soon
Total - 61
Basic notions of Analysis.
• Afonso, A., Nunes, C. (2011). Estatística e Probabilidades. Aplicações e Soluções em SPSS, Escolar Editora.
• Gilda Cunha, Maria do Rosário O. Martins Ricardo Sousa, Filipa Ferraz de Oliveira, Estatística Aplicada às Ciências e Tecnologias da Saúde, Editora LIDEL
• Pedrosa, A. C., Gama, S. M. A. (2004). Introdução Computacional à Probabilidade e Estatística. Porto Editora.
The curricular unit is divided into 6 topics that include lectures and videos of oral exposition of the contents, along with the presentation of examples and complemented by solved proposed exercises. At the end of each topic a revising exercise is delivered. During the curricular unit the students will present one evaluation assignment, contributing for the final grading. A timetable for explaining doubts to students made is available.
Evaluation: exam and assignment (each 50%)
1- Main concepts, definitions and Biostatistics applications
2 - Descriptive statistics: types of data and organizing information
3 - Descriptive statistics: measures of central tendency, measures of dispersion and outliers
4 - Probability theory and applications
5 - Random variables and associated models
6 - Probability distributions
Programs where the course is taught: