You need to activate javascript for this site.
Menu Conteúdo Rodapé
  1. Home
  2. Courses
  3. Physics
  4. Probability and Statistics

Probability and Statistics

Code 14934
Year 2
Semester S1
ECTS Credits 6
Workload TP(60H)
Scientific area Mathematics
Entry requirements Basic notions of Descriptive Statistics.
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 - Brief revision of Descriptive Statistics;
- Combinatorics;
- Probability theory;
- Random variables. Probability distributions;
- Theoretical distributions;
- Interval estimation;
- Hypotheses tests;
- Nonparametric tests;
- Linear regression.
Main Bibliography - Principal:
- Guimarães, R. e Cabral, J. (1997). Estatística. McGraw-Hill.
- Murteira, B., Ribeiro, C., Andrade e Silva, J. e Pimenta, C. (2002). Introdução à Estatística. McGraw-Hill.
- Pedrosa, A. E Gama, S. (2004). Introdução Computacional à Probabilidade e Estatística. Fundação Calouste Gulbenkian. Lisboa.
- Pestana, D. Velosa, S. (2002). Introdução à Probabilidade e à Estatística. Fundação Calouste Gulbenkian. Lisboa.

-Complementary:
- Mood, A., Graybill, F. and Boes, D. (1985). Introduction to the Theory of Statistics. 3rd edition. International Student Edition.
- Draper, N. R. , Smith, H. (1998), Applied Regression Analysis, John Wiley and Sons, 3ª Edição.

Teaching Methodologies and Assessment Criteria The classes will be fundamentally theoretical-practical in nature, combining the exposure of syllabus, with their discussion and application in practical examples. Previously provided notes/slides will be provided for the student to do a preliminary study and in class will be made an exhibition of the main contents.
The more theoretical contents will be presented with the use of practical and concrete examples.
The evaluation of this UC includes the holding two written tests and five mini-tests to be performed on the computer.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2023-10-16

The cookies used in this website do not collect personal information that helps to identify you. By continuing you agree to the cookie policy.