ENBIS-13 in Ankara

15 – 19 September 2013 Abstract submission: 5 February – 5 June 2013

Post-conference Course: Statistical Discovery in Manufacturing

18 September 2013, 14:30 – 18:30

This half-day ENBIS-13 post-conference course will be run by Volker Kraft (JMP Academic Ambassador, Europe). Statistical Discovery describes a journey, which covers both Exploratory Data Analysis (EDA) and Confirmatory Data Analysis (CDA). This practical course focuses on best practices how to tie both fields together to get better results in a shorter time. By a simple to understand process, Statistical Discovery allows you to work more effectively with data, leveraging your contextual knowledge to reliably find answers that reflect real-world ambiguity, uncertainty and compromise. Just as importantly, it allows you to pose relevant, new questions to help shape your approach going forward. Your stakeholders can more easily review and challenge your recommendations, and you can jointly explore alternatives without the distractions of unnecessary or spurious statistical detail. The chosen landscape for this journey is a real-world case study of a pharmaceutical manufacturing process. After introducing the actual quality characteristics and recent process capability, we will aim at improving the process outcome touching - Visualization and exploration of the relationships of process factors and outcomes - Hypotheses generation and modeling techniques to understand how the potential causes operate collectively - Improving the process by finding the best settings - Explore ‘what if’ scenarios to identify the best way forward - Quantify the expected improvement in the light of real-world conditions Most principles taught during this course are not limited to industrial manufacturing, but can be applied to many other analytical contexts as well. Participants are invited to bring their laptops (Windows or Mac) into the class to join our guided tour. Beforehand JMP can be installed free of charge to enjoy this journey while sitting in the first row.

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