"Let’s not kid ourselves: the most widely used piece of software for statistics is Excel."
This quote of B.D. Ripley soberly describes
the state of demand for statistical software nowadays. Not only students
of economics, management science and related fields but particularly
the industry asks for intuitive, efficient and secure software for
statistical data analysis. But not for the sake of high implementation costs
and the overhead of a steep learning curve.
Although Excel is the favourite number cruncher it is limited in
several ways (for more information see e.g. McCullough B.D., Wilson, B., “On
the accuracy of statistical procedures in Microsoft Excel 2000 and Excel
XP”, in Computational Statistics & Data Analysis, 40 (2002), pp.
How to solve the dilemma of having intuitive graphics and data handling
on the one hand and retrieving reliable results on the other hand?
You have a heterogeneous client/server environment? You have a need for distributed computing?
You develop statistical methods on Unix, Linux, Mac and Windows? Or you wish you could?
Your users ask for methods to be also available on Excel for Windows?
You want to provide a scalable method- and database on high-performance servers and grant Excel users access to these?