Software

B-Course 2.0 by Complex Systems Computation Group (CoSCo) (http://b-course.hiit.fi)

We are happy to announce version 2.0 of the B-Course Data Analysis service (http://b-course.hiit.fi) which has thousands of users world-wide in various application areas. B-Course is built on an ASP architecture and it can be used with regular Internet browsers. New features added to this edition of B-Course include Classification Trail and inference with Soft evidence. B-Course can be freely used for educational and research purposes.

B-Course summary:

B-Course is a web-based data analysis tool for Bayesian modeling, in particular dependence and classification modeling. It can also be used as an interactive tutorial which provides you with data sets that have been prepared in advance. B-Course can be used as an analysis tool for any research where dependence or classification modeling based on data is of interest.

B-course is motivated by the problems in the current statistical practice. When applied by practitioners, in many cases the underlying assumptions and restrictions are not clear to the user, and the complicated nature of the software encourages the users to "black box" approach where default parameter values are used without any understanding of the actual modeling and analysis task. This has lead to the situation where frequently the conclusions derived from the analysis are far from the intended plausible reasoning. B-Course is an attempt to offer a multivariate modeling method that can also be understood by applied practitioners. It is a step in this direction and consequently can definitely be improved upon. However, it makes a serious attempt to give an informal introduction to the approach. Finally, one should not be misguided by the tutorial nature of B-Course. With the restrictions stated in the support material, in its own class B-Course is a powerful analysis tool that can (and hopefully will) be expanded to address some of its current limitations.

B-Course is designed for non-computer science professionals in mind, for researchers in social sciences, medicine, biology etc. Therefore it provides a sophisticated user interface (which by the way also is usable by almost any browser we are aware of) with very few parameter settings. It allows automatic intelligent uploading of user's data sets over the network and provides intelligent parsing and discretization of the data sets.