An introduction to R (fall edition) - 2015


This course is going to be related to data analysis with the R language. It will be directed to people with no idea or a starting knowledge of R. The main objectives of the course will be: 1) know how to install and run R in your computer (Linux, Mac or PC), working with different text editors (Emacs and RStudio); 2) know how to install different packages related to your own work; 3) know how to work with objects and data.frames; 4) write scripts with R; 5) import data from other programs (i.e XL); 5) work with dates; 6) perform basic statistical analysis and modeling with R; and 7) plot basic graphs with R.

Programme information: 

  • Monday (2 hours theory + 2 hours practical + 2 hours of personal study) Introduction to R. Installing R. Emacs or RStudio. The editor, the console and the graphical environment on R. Simple plots in R. The help in R. Surfing through the web. R objects. Working with vectors. Some examples. Data frames. Some examples. How to read files from other programs (XL,…)
  • Tuesday (2 hours theory + 2 hours practical + 2 hours of personal study). Functions in R. Introduction to statistics in R. Mean, standard deviation, standard error, some basic statistics test in R. Data transformation.
  • Wednesday (2 hours theory + 2 hours practical + 2 hours of personal study) Linear regression models in R. Quartile regression. Multiple regression models. Paired T-tests. ANOVA, ANCOVA.
  • Thursday. (2 hours theory + 2 hours practical + 2 hours of personal study) Hands on data I, working with your own data. Hands on data II, plotting your own data.
  • Friday (2 hours theory + 2 hours practical + 2 hours of personal study). Bioconductor an interesting tool in R for molecular biology.

Past course editions: 

This course is also taught in spring. Please, have a look at the spring edition here.

Number of hours: 




Course dates: 

Monday, September 14, 2015 to Friday, September 18, 2015


9:00-12:30 h


Institut de Ciències del Mar

Maximum number of places: 


Lab or field work description: 

If you have own data bases to work with, please bring them to the course. You will start to work with them.

Special requirements: 

No special background is needed, but it would be preferable to have a minimum statistical knowledge (i.e. an introductory course during your BSc.)

Laptop or notebook computer: Linux, Mac and PC are all welcomed.

Contact for further information: 

For additional information, please check our Contact section or get in contact directly with the Lecturer of this course.


Full price of this course is 340€. A reduced registration fee of 285€ is applied for early registrations (20 days before the opening of the course).
Price: 340.00€

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