1.3 Why this software?

There are many advanced commercial statistical software, such as SPSS, Excel (with commercial add-ons), Minitab, Stata, SAS, etc. We will rely on the combo R (R Core Team 2015) + R Commander (Fox 2005) due to some noteworthy advantages:

  1. Free and open-source. (Free as in beer, free as in speech.) No software licenses are needed. This means that you can readily use it outside UC3M computer labs, without limitations on the period or purpose of use.

  2. Scalable complexity and extensibility. R Commander creates R code that you can see, and eventually understand. Once you begin to get a feeling of it, you will realize that is faster to type the right commands than to navigate through menus. In addition, R Commander has 39 high-quality plug-ins (September, 2016), so the procedures available through menus will not fall short easily.

  3. R is the leading computer language in statistics. Any statistical analysis that you can imagine is already available in R through its almost 9000 free packages (September, 2016). Some of them contain a good number of ready-to-use datasets or methods for data acquisition from accredited sources.

  4. R Commander produces high-quality graphs easily. R Commander, through the plug-in KMggplot2, interfaces the ggplot2 library, which delivers high-quality, publication-level graphs (sample gallery). It is considered as one of the best and more elegant graphing packages nowadays.

  5. Great report generation. R Commander integrates R Markdown, which is a framework able to create .html, .pdf and .docx reports directly from the outputs of R. That means you can deliver high-quality, reproducible and beautiful reports with a little amount of effort. For example, these notes have been created with an extension of R Markdown.

In summary, R Commander eases the learning curve of R and provides a powerful way of creating and reporting statistical analyses. An intermediate knowledge in R Commander + R will improve notably your quantitative skills, therefore making an important distinction in your graduate profile (it is a fact that many social scientists tend to lack a proper quantitative formation). So I encourage you to take full advantage of this great opportunity!

References

R Core Team. 2015. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Fox, John. 2005. “The R Commander: A Basic Statistics Graphical User Interface to R.” Journal of Statistical Software 14 (9): 1–42. http://www.jstatsoft.org/v14/i09.