Scientific area: Information and Communication Technologies
Total working hours: 130
Total contact time: 20
The aim of this course is to develop in the students skills to deal with problems involving optimization methods, simulation techniques and data visualization techniques.
R Language Optimization Simulation Visualization
Upon completion of this unit, the student should be able to:
• Recognize the role and importance of the tools available in R for processing and analyzing statistical data;
• Identifying and learning to apply the main methods of optimization used in statistics;
• Develop and apply simulation techniques;
• Identified and exploring visualization techniques;
• Solve problems using the R program, involving the themes dealing with statistics.
1.Programming in R
2.Optimization in Statistics
Christian P. Robert and George Casella (2010): Introducing Monte Carlo Methods with R, Springer-Verlag . ISBN 978-1-4419-1575-7
Maria L. Rizzo (2008): Statistical Computing with R, Chapman and Hall/CRC. ISBN: 9781584885450, ISBN 10: 1584885459.
J. E. Gentle (2005): Random Number Generation and Monte Carlo Methods 2nd Edition, Springer. ISBN 0-387-0017-6 e-ISBN 0-387-21610
Everitt, E.S. (1987): Introduction to Optimization Methods and their Application in Statistics, Chapman and Hall, ISBN:-13. 978-94-010-7917-4, e-ISBN-13: 978-94-009-3153-4, DOI: 10.1007/978-94-009-3153-4
E-learning (fully online).
Evaluation is made on individual basis and it involves the coexistence of two modes: continuous assessment (60%) and
final evaluation (40%). Further information is detailed in the Learning Agreement of the course unit.
Pre-requisites: not applicable
Language(s) of Instruction: Portuguese.
Contact for virtual mobility students: Communication and International Relations Office – email@example.com