Partner Associations

ENBIS is cooperating with the following associations:
ISBIS logo
ISBIS is an international society that is dedicated to the promotion of business and industrial statistics worldwide. It is part of a family of international associations that operate under the umbrella of the International Statistical Institute (ISI).
 
 
Cooperation between ENBIS and the French Statistical Society (FSS) started at the 2011 Annual Conference of ENBIS in Coimbra (Portugal) with a special session dedicated to discussion of advances in business and industrial statistics in France. In the administrative meeting held in Coimbra representatives of both organizations agreed not only to participate at each other's future events (bENBIS is currently organizing a special ENBIS session in the framework of the FSS's spring conference in Brussels) but also to further strengthen cooperation with (1) promotion of each other's activities through available communication channels and (2) development of joint publications.
 
 

The ECAS courses are intended to achieve postgraduate training in special areas of statistics for both researchers and teachers at universities. Also professionals working in industry and interested in the application of new statistical methods are invited to participate.

Cooperation between ECAS and ENBIS started with the school entitled “Big Data in Business and Industry”, taking place just before the ENBIS-17 conference. The school was fully booked, so ECAS and ENBIS signed a convention (ending on 31st March 2024) to organise events in a similar format.

The primary audience for the ECAS-ENBIS courses consists in—but is not limited to—phd students, young doctors, young practitioners. More experienced attendees are also welcome.

 

ISEA

The objectives of ISEA are to advance the theory and practice of statistical engineering, including its insertion into academic curricula, and to enhance the professional qualifications and standing among its members.

Statistical engineering is the discipline dedicated to engineering solutions to problems of a statistical nature, particularly to large, complex, and unstructured problems.