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Biostatistics

Code 12510
Year 2
Semester S2
ECTS Credits 6
Workload TP(60H)
Scientific area Mathematics
Entry requirements Knowledge of real analysis.
Mode of delivery Face to Face.
Work placements Not applicable
Learning outcomes At the end of the curricular unit, students should be able to:

- Obtain basic knowledge of Probability and Statistics, vital for future learning of more advanced concepts that arise in the course of academic and/or professional training.
- Select and apply proper statistical methods to draw conclusions under uncertainty in Optometry and Vision Science.
Syllabus 1. Brief review of Descriptive Statistics

2. Basic concepts of probability
- Random Experience, sample space and events.
- Classical definition of probability.
- Axiomatic definition of probability and its consequences.
- Conditional probability and independence of events.
- Real discrete and continuous random variables and therir probability distributions.
- Distribution moments.
- Characterization of some discrete and continuous probability distributions.
- Central Limit Theorem and its applications.

4 Introduction to statistical inference
- Point estimation and estimator properties
- Confidence Intervals
- Parametric and non-parametric hypothesis tests
Main Bibliography - Murteira, B., Ribeiro, C., Silva, J.A. and Pimenta, C. (2010). Introdução à estatística. Escolar Editora.
- Hall, A., Neves, C. and Pereira, A. (2011). Grande Maratona de Estatística no SPSS. Escolar Editora.
- Ross, S. (2009). Introduction to probability and statistics for engineers and scientists. Amsterdam Elsevier.
Teaching Methodologies and Assessment Criteria The assessment of knowledge is done during the semester with two written tests and if students do not reach the expected skills the evaluation is done by a written exam at the end of the semester.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2016-06-09

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