ENBIS 2019

Events

The 19th annual conference of the European Network for Business and Industrial Statistics will be hosted by the Department of Probability Theory and Statistics at the Eötvös Loránd University, Budapest and will take place from the 2nd to 4th of September, 2019.

The annual conference session topics include but are not limited to, the special areas of interest that exist within ENBIS (formalised in the so-called Special Interest Groups). The non-exhaustive list includes:
•Design of Experiments
•Measurement Uncertainty
•Process Modeling and Control
•Reliability and Safety
•Statistics in the Pharmaceutical Industry
•Statistical Computing
•Operational Risk Management
•Statistics in Practice
•Stochastic Modelling
•Quality Improvement and Six Sigma
•Data Mining and Warehousing
•Machine Learning
•Predictive Analytics
•Statistical Education for Business and Industry
•Business and Finance

The annual conference also features distinguished keynote speakers, special thematic sessions, workshops and panel discussions, as well as pre- and post-conference courses and an industrial visit.

Confirmed keynotes for the ENBIS-19 conference in Budapest are:
•Christine M. Anderson-Cook (Los Alamos National Laboratory, USA), on “Big Decisions: How Statisticians Can Contribute”.
•Andrea Saltelli (University of Bergen, Norway), on “Sensitivity Analysis. An introduction”.

Pre- and post conference courses will be held on topical subjects: New Product Growth Models, Causality, Functional Data Analysis and Random Forests.

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Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.