Computational Statistics

Cod: 21043

Department: DCET

Department: DCET

ECTS: 6

Scientific area: Mathematics

Scientific area: Mathematics

Total working hours: 156

Total contact time: 26

Total contact time: 26

The computational developments applied to Statistics allow approaches and solving problems that once would be impractical. This is an area that has had great growth and utility in various applications and research. It is intended so in this unit, students gain knowledge in the area of Computational Statistics using the software R. Besides an revision of R language, will be done an introduction to simulation topics, applications of the Monte Carlo methods (MC), Linear Regression and Analysis of Variance.

R Language

Random variables

Simulation

Resampling

Random variables

Simulation

Resampling

• Describe and illustrate the use of pseudo-random number generators (NPAs) and random variables;

• Apply Monte Carlo methods in different contexts;

• Distinguish the Bootstrap and Jacknnife Resampling methods;

• Describe the method of least squares and to analyze the degree of association between two variables.

• Apply the Analysis of Variance technique in the comparison of groups.

• Solve problems involving the topics covered.

• Apply Monte Carlo methods in different contexts;

• Distinguish the Bootstrap and Jacknnife Resampling methods;

• Describe the method of least squares and to analyze the degree of association between two variables.

• Apply the Analysis of Variance technique in the comparison of groups.

• Solve problems involving the topics covered.

1. Introduction of R language

2. Generation of pseudo-random numbers and random variables

3. Statistical Inference and Monte Carlo methods

4. Regression and Analysis of Variance

5. Resampling methods

2. Generation of pseudo-random numbers and random variables

3. Statistical Inference and Monte Carlo methods

4. Regression and Analysis of Variance

5. Resampling methods

- Oliveira, A., Oliveira, T.A. (2019).
*Estatística Computacional.*Texto de Apoio. - Maria L. Rizzo (2008):
*Statistical Computing with R*, Chapman and Hall/CRC. ISBN: 9781584885450, ISBN 10: 1584885459. - Christian P. Robert and George Casella (2010):
*Introducing Monte Carlo Methods with R*, Springer-Verlag . ISBN 978-1-4419-1575-7 - Chiahara, L.M., Hesterberg, T.C. (2011): Mathematical Statistics with Resampling and R, Wiley, ISBN: 978-1-118-02985-5

E-learning

Continuous assessment is privileged: 2 or 3 digital written documents (e-folios) during the semester (40%) and a
presence-based final exam (p-folio) in the end of the semester (60%). In due time, students can alternatively choose to perform one
final presence-based exam (100%).

Pre-requisites: not applicable

**Language(s) of Instruction: **Portuguese.

**Contact for virtual mobility students: **Communication and International Relations Office – gcri@uab.pt