| Code |
14900
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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 |
Differential and integral calculus in R
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Mode of delivery |
Face to face.
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Work placements |
Not applicable.
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Learning outcomes |
The aims of this Course Unit are:
- Encourage critical skills in constructing confidence intervals, formulating hypotheses and prediction and interpreting results;
- Encourage the application of probabilistic and statistical methods and techniques;
-Basic - Demonstrates general culture for the Probability and Statistics: historical evolution of concepts; expertise critical sense in arguing ideas.
-Scientific - Demonstrates knowledge of basic Math applied to Informatics; demonstrates basic knowledge of Probability and Statistics
-Operational - Know and dominates the basic mathematical language used in Probability and Statistics;
-Cross Outcomes - Understands and demonstrates general principles of ethics and morality, ability for teamwork, ability to keep records organized.
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Syllabus |
1. Brief introduction to R software.
2. Introduction to Probability Theory: axioms and properties of probability, conditioning and independence; discrete and continuous real random variables, distribution function, probability function and probability density function, Binomial, Geometric, Poisson, Normal distributions, moments and Central Limit Theorem.
3. Introduction to Statistical Inference: point estimation; confidence intervals; parametric and nonparametric hypothesis tests; linear regression.
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Main Bibliography |
- Gonçalves, M. E., Nogueira, M. E. e Rosa, A. C. (2020). Probabilidades e estatística para ciências e tecnologia: conceitos e exercícios resolvidos. Edições Almedina. Cota: M-7.0-00029.
- Morais, M. C. (2023). Probabilidades e Estatística. Teoria, Exemplos e Exercícios. Coleção Ensino da Ciência e da Tecnologia. IST Press.
- Montgomery, D. e Runger, G. (2011). Applied statistics and probability for engineers, 5ª Edição, John Wiley & Sons. Cota: MD-14-00531
– 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 classes are of a theoretical-practical nature with exposition of the fundamental concepts of Probability Theory and Statistical Inference, exemplified with problems in the field of engineering, and problem solving, by students with professor guidance, with applications to the field of engineering.
The assessment is continuous, consisting of two written tests and 5 minitests carried out on the computer.
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Language |
Portuguese. Tutorial support is available in English.
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