Biostatistics

Recommended Prerequisites

Basic knowledge of Mathematics.

Teaching Methods

The classes are based on the discussion of examples (using real or simulated data) and exercises to apply the material being taught. Mathematical complexities will be kept to a minimum.

Learning Outcomes

The main goal is studying exploratory data analysis methods, data collection methods and the main inferential statistics methods. The student should develop the ability to interpret results and to critically evaluate the methods used. The analysis of real data will receive considerable attention.

Work Placement(s)

No

Syllabus

Introduction to Biostatistics: Exploratory data analysis vs. Inferential statistics
1. Producing data
2. Exploratory data analysis
3. Introduction to Probability
4. Probability distributions: normal and binomial models
5. Confidence intervals for proportions and means
6. Hypothesis testing for proportions and means
7. Comparing the means of two populations
8. Frequencies analysis: chi-square tests
9. Analysis of Variance (ANOVA)
10. Simple linear regression
11. Nonparametric tests.

Head Lecturer(s)

Manuel António Facas Vicente

Assessment Methods

Assessment
There are two types of grading: during the semester or by final exam. During the semester there are two mid-term exams (100% of the final grade): 100.0%

Bibliography

Biostatistics: a foundation for analysis in the health sciences
Daniel, W.W. (Wiley, 2010)
Estatística, notas de apoio às aulas
Tenreiro, C. (Coimbra, 2009)
http://arquivoescolar.org//handle/arquivo-e/198
Introduction to the practice of statistics
Moore, D.S., McCabe, G.P. ( W. H. Freeman, 2006)
Basic & clinical Biostatistics
Dawson, B., Trapp, R.G. ( McGraw-Hill, 2001).