Home
Courses
Web, Mobile and Cloud Computing
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 and Normal distributions; Properties of the sample mean. 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)
Language	Portuguese. Tutorial support is available in English.