Overall objectives:

1 - The main goal of this unit is that students know and exploit the potential of the (free and open source) R language/software (Chapters I, II and III).
2 - Moreover, they are expected to extend the range of knowledge in statistical estimation and simulation (Chapters IV and V).
3 - Thus, students are provided with a statistical tool that will allow them in the future to solve problems in their area without the need to invest in statistical and / or mathematical software. A brief foray into programming (Chapters I, IV, V and VI) aims to develop skills in students so that they can face new challenges, particularly with regard to unsolved problems in traditional statistical software.

Syllabus:

1 - The syllabus is organized into six chapters: P1 - What is R? Getting Started
2 - P2 - The R Commander: A graphical environment
3 - P3 - Statistical Review with the resource R
4 - P4 - Maximum likelihood and the EM algorithm
5 - P5 - Simulation: Monte Carlo method.
6 - P6 - R: advanced topics

Literature/Sources:

Landau, David P. e Binder, Kurt , 2005 , A guide to Monte Carlo simulations in statistical physics , Cambridge University Press
Braun, W. John e Murdoch, Duncan J. , 2007 , A First Course in Statistical Programming with R. , Cambridge University Press
Dalgaard, Peter , 2002 , Introductory Statistics with R , Springer, New York
Dennis, Brian , 2013 , The R Student Companion , The R Series, CRC Press, Taylor & Francis Group
Fox, John , 2005 , The R Commander: A Basic-Statistics Graphical User Interface to R , Journal of Statistical Software
Maindonald, John e Braun, John , 2003 , Data Analysis and Graphics Using R - an Example-based Approach , Cambridge University Press
McLachlan, G.J. e Krishnan, T , 1997 , The EM Algorithm and Extensions , John Wiley, New York
Torgo, Luís , 2009 , A Linguagem R. Programação para a análise de dados , Escolar Editora
Xie, Yihui , 2014 , Dynamic Documents with R and knitr , CRC Press, Taylor & Francis Group

Assesssment methods and criteria:

Classification Type: Quantitativa (0-20)

Evaluation Methodology:
M1-The lectures are expository using the computer and the projector and interactive given the nature of the UC and the number of students. Thus, students are frequently encouraged to intervene in order to discover for themselves the way to go. This way it is hoped to instill the independence spirit and competence. M2-The theoretical/practical classes are designed to solve problems in R by students. However, there is an individual supervision and, if necessary, a general explanation. M3-This course can be seen as a good test for future professionals in statistics and as such, it is proposed to students to carry out two projects, individual or group (up to three students) with oral presentation: one in the form of a poster and the other in the form of an article, weighted with 20% and 30% respectively. M4-Finally, there is an individual assessment with theoretical and applied part (50% weighting).At appeal/improvement period, students can only recover the part relating to the frequency.