Checking date: 18/04/2024

Course: 2024/2025

Programming II
Bachelor in Statistics and Business (Plan: 400 - Estudio: 203)


Department assigned to the subject: Computer Science and Engineering Department

Type: Compulsory
ECTS Credits: 6.0 ECTS


Requirements (Subjects that are assumed to be known)
Programming I
Skills and learning outcomes
Description of contents: programme
1 Data Structures 2 Programming Structures 2.1 Conditional structure: if 2.2 Structures of loops: for, while, repeat 3. Programming Structures 4. Functions 4.1 Definition of functions 4.2 Variables and parameters in functions 4.3 Infix notation 4.4 Function calls 5. Recursive functions 6.Input, output and data storage (keyboard, files) 7.Graphics
Learning activities and methodology
The subject will be taught in theory classes through master classes and practical exercises, and the practical classes through tutored classes. The master classes will be focused so that the student acquires the knowledge about programming necessary for his professional development. The practical classes will be developed so that, in a tutored way, the student acquires skills in the analysis, design, development, testing and documentation of programs.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100

Calendar of Continuous assessment

Extraordinary call: regulations
Basic Bibliography
  • Andrie de Vries and Jories Meys. R for dummies. John Willey & Sons. 2015
  • Crawley, Michael J. Statistics : An Introduction Using R. John Wiley & Sons. 2005
  • Dalgaard, Peter. Introductory statistics with R. Springer . 2002
  • Everitt, Brian. A handbook of statistical analyses using R. Chapman & Hall/CRC. 2006
  • Grolemund, G., Wickham, H.. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data.. O'Reilly. 2016
  • Lander, J. R for Everyone: Advanced Analytics and Graphics. Addison-Wesley Data and Analytics. 2017
  • Maindonald, John Hilary. Data analysis and graphics using R : an example-based approach. Cambridge University Press. 2003
  • Norman Matloff. The Art of R Programming: A Tour of Statistical Software Design. William Pollock. 2011
  • Rizzo, Maria L. Statistical computing with R. Chapman & Hall/CRC. 2007
  • Vries, A., Meys, J. . R for dummies. A Wiley Brand . 2017
Recursos electrónicosElectronic Resources *
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The course syllabus may change due academic events or other reasons.