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Code 13639
Year 1
Semester S2
ECTS Credits 6
Workload TP(60H)
Scientific area Mathematics
Entry requirements Integral and Differential Calculus.
Mode of delivery Face to face.
Work placements Not applicable.
Learning outcomes Identify and apply, in problems of sciences and technologies, strategies of Probability and Statistical Inference.
At the end of this UC the students should be able to choose and apply statistical techniques to real problems in the biological and health sciences.
Syllabus 1. Introduction to Probability Theory: Independence and conditioning; Distributions Binomial, Hypergeometric, Geometric, Poisson, Normal; Moments and the Central Limit Theorem. 2. Introduction to Statistical Inference: estimation by the method of moments; properties of estimators; confidence intervals; tests of hypotheses.
Main Bibliography Introdução Computacional à Probabilidade e Estatística, Pedrosa, A. e Gama, S. (2007) Porto Editora.

Introdução à Probabilidade e Estatística, Vol.1, Pestana D. e Velosa S., 2006, Fundação Caloust Gulbenkian.

Teaching Methodologies and Assessment Criteria The periodic evaluation consists of two written tests whose average greater than 9.5 exempts the student from the final evaluation. The final evaluation consists of a written exam.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2021-06-18

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