You need to activate javascript for this site.
Menu Conteúdo Rodapé
  1. Home
  2. Courses
  3. Web, Mobile and Cloud Computing
  4. Statistics and Data Analysis

Statistics and Data Analysis

Code 16218
Year 1
Semester S2
ECTS Credits 6
Workload TP(60H)
Scientific area Mathematics
Entry requirements Differential and integral calculus
Learning outcomes At the end of the course unit the student should:
- know how to select and apply probability and statistical techniques to solve problems in the field of Web-focused Computer Science;
- be able to take part in studies involving the statistical processing of data, using R software, and interpret the results obtained.
Syllabus 1. Descriptive statistics: frequency tables and graphical representations for one- and two-dimensional statistical variables; descriptive measures.
2. Introduction to Probability Theory: properties of a probability; independence of events; conditional probability; Binomial, Hypergeometric, Geometric and Normal distributions; moments and the Central Limit Theorem.
3. Introduction to statistical inference: point and interval estimation; hypothesis testing.
4. Simple linear regression: least squares method.

Main Bibliography - Figueiredo, F., Figueiredo, A., Ramos, A. e Teles, P. (2009). Estatística Descritiva e Probabilidades Problemas Resolvidos e Propostos com Aplicaçõees em R. Escolar Editora. Cota: EG-4.2-00440
- Gonçalves, E., Nogueira, E. e Rosa, A.C. (2016). Probabilidades e Estatística para Ciências e Tecnologia. Conceitos e exercícios resolvidos. Almedina. Cota:M-7.0-00028
- Montgomery, D. e Runger, G. (2011). Applied statistics and probability for engineers, 5ª Edi¸c˜ao, 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)
Teaching Methodologies and Assessment Criteria The classes are theoretical-practical, in which the student will be guided to the resolution of exercises involving statistical inference techniques, using SPSS whenever necessary.

The assessment of knowledge and skills acquired by students during the teaching-learning process is done by means of two tests (F_1 and F_2, rated from 0 to 20) with a weighting of 0.5 each.

The final teaching-learning classification (CEA,,expressed in 0 to 20 values) is calculated as follows

Final exam exemption is granted when the CEA is equal to or higher than 9.5 points, requiring a minimum score of 3 points in each test. The grade of ``FREQUENCY'' is awarded.when CEA is less than 9,5 points.

Grades above 18 points are defended with an oral exam.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2024-04-22

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