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International Statistical Engineering Association

ENBIS Spring Meeting 2019

  • 13 Jun 2019
  • (UTC-04:00)
  • 14 Jun 2019
  • (UTC-04:00)
  • Barcelona Spain

ENBIS Spring Meeting 2019
Organized with ISEA

The European Network for Business and Industrial Statistics (ENBIS) Spring Meeting will be organized together with ISEA. It will take place on June 13th and 14th 2019 in Barcelona, Spain, and is hosted by UPC|BarcelonaTech. Register at

Aim of Meeting

Statistical engineering pursues the systematic study of how to solve complex problems using data. As the problems to be solved are complex, the solution often requires the integration of different approaches: statistical concepts and tools, but also other knowledge from relevant disciplines. The aim of the meeting is discussing on the emerging discipline of statistical engineering. The following questions will be explored:

  • What is statistical engineering, and why it is the right time for it?
  • Why is statistical engineering different from applied statistics or data science?
  • How did the idea originate and evolve?
  • What are some case studies of statistical engineering?
  • What's in it for European professionals and companies?

Structure of Meeting

Several keynotes will give presentations during Thursday and Friday mornings, followed by discussants. Contributed papers will be presented on Thursday afternoon. Of course, there'll also be time for informal discussions and networking.

Call for abstracts!

Submissions are accepted from 15 January – 15 April 2019. Topics of substantial interest include:

  • Applications of statistical engineering to real problems
  • Strategies for approaching complex problems with data
  • Development of the underlying theory of integration of multiple methodologies
  • Case studies on working together in interdisciplinary teams to solve complex problems
  • Case studies and discussions on the role of the scientific method in solving actual complex problems
  • Discussions on how statistical engineering can enhance data science
  • Discussions of the role of historical data and observational studies in statistical engineering
  • Discussions on how to create sustainable solutions

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