Course with R: is it worthwhile?

Even if you don’t use R now you will benefit
from a course where R is used.
Find out, why.

Even if you don’t use R now you will benefit from a course where R is used.

  • Data analysis methods introduced during our courses are best practices and are accessible in various software tools. We deal with R to illustrate them.
  • Thanks to using R during a course you will be equipped with knowledge and practical skills independent of commercial software.
  • It is beneficial to know powerful and enormous tool that is R.

Nevertheless, if you are not interested in a training with use of R then you can order an in-house training with another tool or even without hands-on computer workshops.

Link to R web site:


  • R is used in many world-wide operatong companies (see an interesting article from The New York Times).
  • It is a main software of choice in many companies.
  • Even if companies use foremost big commercial systems then for some tasks they use R.
  • We know from experience that R is used in majority of banks.
  • Knowledge of R is often required by employers.
  • Popularity and acceptance for R are continuously increasing (an interesting post about popularity of SAS, SPSS, and R).
  • Companies developing data analysis software appreciate R and allow accessing it from their tools:


  • It is free to all business and scientific applications (with exception of some packages).
  • It works on many Operating Systems.


  • Consecutive steps of data analysis are written in a file (script). This allow easy reproducing of the results got.
  • This allows any automation of any analysis.
  • R programming language is extraordinarily comfortable and flexible.
  • There are software programs facilitating work with R, for example:

Selection of methods

  • Working with R you can analyze any data from any field using practically any method (CRAN Task Views).
  • About 4.000 of packages accessible in official distribution of R (May 2012) and more not official ones.
  • Data analysis methods are not ”black box” methods: their source code is always accessible.
  • R is ”common language” (”lingua franca”) of modern statistics: authors of scientific articles introducing new data analysis methods often attach to them R codes.

Our experience

  • We have been used R for many years: in research and commercial projects, in academic teaching and during trainings.
  • We cannot imagine as comfortable work as in R in any other, free or commercial tool.
  • We teach R and use for teaching at universities.

Other advantages

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