Commercial meets Open Source- Tuning STATISTICA with

R is an extremely powerful environment for statistical computing: It provides packages designed for different areas such as data mining, econometrics, epidemiology, biostatistics, it offers methods from different statistical disciplines like time series analysis, statistical process control, bootstrapping, cluster analysis, and others. Besides its mere extent, R differs from competing statistics environments also in the fact that it reflects the state-of-the-art in statistical sciences. And not to forget: R is freely available. On the other hand, R is not particularly user-friendly: It does not offer a graphical user-interface, where the repertoire of methods is fully integrated and available also for users, who have not learnt the R language. It does not offer a powerful spreadsheet environment, which enables an intuitive way of data manipulation. Therefore, (potential) users from applied sciences and industry often do not have the heart to work with R. In this talk, I propose to combine the power of R with the comfort of a commercial pack-age like STATISTICA. STATISTICA can be used as an easily operated interface with a respectable basic equipment of statistical procedures, see Weiß (2006). But if required, on