Code |
14900
|
Year |
2
|
Semester |
S1
|
ECTS Credits |
6
|
Workload |
TP(60H)
|
Scientific area |
Mathematics
|
Entry requirements |
Differential and integral calculus in R
|
Mode of delivery |
Face to face.
|
Work placements |
Not applicable.
|
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.
|
Syllabus |
1. introduction to probability theory: axiomatics and properties of probability, conditioning and independence; real random variables, binomial, geometric, Poisson, exponential and normal distributions; moments and the central limit theorem. 2. Introduction to Statistical Inference: point estimation; confidence intervals; parametric and non-parametric hypothesis tests; linear regression.
|
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. - Pedrosa, A. e Gama, S. (2004). Introdução computacional à probabilidade e estatística. Porto Editora. Cota: I-8.0-00013
- 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 theoretical-practical in nature, in which the student will be guided to solve exercises involving probability and statistical inference techniques.
The knowledge and skills acquired by the students during the teaching-learning process will be assessed by means of two tests (F1 and F2), graded from 0 to 20 points, each weighted at 0.5. The final teaching-learning grade (CEA), from 0 to 20 points, is calculated as follows: CEA = 0, 5F1 + 0, 5F2. Exemption from the final exam is granted when the CEA is equal to or higher than 9.5, with a minimum mark of 4 (from 0 to 20) in each test and attendance of more than 80%. The “NOT ADMITTED” classification is awarded when the final teaching-learning classification is lower than 4.
Tests will be held on the following dates: 1st test 30/10/2024 at 18h 2nd test 18/12/2024 at 18h
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Language |
Portuguese. Tutorial support is available in English.
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