| Code |
13437
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| Year |
2
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| Semester |
S1
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| ECTS Credits |
6
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| Workload |
TP(60H)
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| Scientific area |
Mathematics
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Entry requirements |
Integral and Differential Calculus.
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Mode of delivery |
Face-to-face.
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Work placements |
Not applicable.
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Learning outcomes |
To apply strategies of Statistical Inference.
At the end of this UC students should be able to:
a) identify issues of science and biological and medical technologies that can be solved with probability strategies and statistical inference;
b) build probabilistic models appropriate to the problems;
c) select and apply strategies of Statistical Inference in solving problems.
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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.
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Main Bibliography |
Principal Bibliography:
Probabilidades e Estatística para Ciências e Tecnologia.(2016) Esmeralda Gonçalves, Ana Cristina Rosa e Maria Emília Nogueira. Editora Almedina.
Complementary Bibliography:
Pestana, D. e Velosa, S. (2010). Introdução à probabilidade e à estatística, 4ª Ed., Fundação Calouste Gulbenkian. Cota: I-0.0-00025
Ross, S. (2009). Introduction to probability and statistics for engineers and scientists. Amsterdam Elsevier. Cota: F-1.8-01370 (CD)
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Teaching Methodologies and Assessment Criteria |
The periodic evaluation consists of two written tests, 10 points each. Obtaining at least 3 points in each test and 9.5 points in total or more exempts the student from the final evaluation. The final evaluation consists of a written examination.
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Language |
Portuguese. Tutorial support is available in English.
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