SFB 649 Discussion Paper 2006-071 Color Harmonization in Car Manufacturing Process Anton Andriyashin* Michal Benko* Wolfgang Härdle* Roman Timofeev* Uwe Ziegenhagen* * Institute for Statistics and Econometrics, School of Business and Economics,...

Modern statistical computing requires smooth integration of new algorithms and quantitative analysis results in all sorts of platforms such as webbrowsers, standard and proprietary application software. Common statistical software packages can often not be adapted to integrate into new...

Die vorliegende Doktorarbeit bündelt die Veröffentlichungen des Autors und seiner Koautoren zu den Themen e-Learning und statistischer Software. Die Kapitel 2 bis 5 sind Aspekten des e-Learning gewidmet, die Kapitel 6 bis 9 beschreiben die Entwicklung der statistischen Programmiersprache...

Students of introductory courses consider statistics as particularly difficult,as the understanding of the underlying concepts may require more time andenergy than for other disciplines. For decades statisticians have tried to enhanceunderstanding with the help of technical solutions such as...

Along with many others, we agree that a modern education in statistics needs toincorporate the practical analysis of real datasets, which are usually more complex than the common examples found in standard textbooks. The software used in the teaching of statistics includes standard spreadsheet...

Modern computing equipment is present at schools and universities at all levelsof education. 4 In the statistical sciences computers offer great opportunities toenrich the learning process by the means of e.g. animations, software integrationor on-the-fly computations. A personal review of...

Without doubt modern education in statistics must involve practical, computer-based data analysis but the question arises whether and how computational elements should be integrated into the canon of methodological education. Should the student see and study high-level programming code right at...

Statistical research has always been at the edge of available computing power. Huge datasets, e.g in DataMining or Quantitative Finance, and computationally intensive techniques, e.g. bootstrap methods, always require a little bit more computing power than is currently available. But the most...