Data handling, DoE and Statistical Analysis 

About the course:

DoE and statistical analysis are central in various kinds of research and development work. However, established techniques are unfortunately often considered to be difficult to use and are therefore not easily accessible for many non-experts. In this course, we will show that this is not true. We have built a course around the famous Pareto principle, which is a mathematical distribution that states that 80% of all outcomes are derived from 20% of causes. This “law” also has other names such as the law of the vital few or the principle of factor sparsity. Within this context, we hope to show that by knowing 20% of the theory,  we will enable 80 percent of the potential of the topics of the course and thereby teach you the skills to make use of the tools that digitization have to offer. In the course, we will teach through demonstration on relevant examples for material scientists which in the end hopefully will be relevant for you to use on your own research data.

After passing the course, You should be able to:

•             design and evaluate experimental designs for full and reduced two-level factorial experiments,

•             construct models for process outcomes and validate these,

•             explain the advantages, disadvantages, risks and limitations of different methods in order to assess whether and when the statistical methods are applicable,

•             use statistical software for planning, processing and analysis of multivariate data from different sources,

•             choose appropriate tools based on the purpose of an investigation, as well as given amount of data and its complexity, and apply them for compilation, processing, analysis and presentation through written and oral presentation.

The course will be given by Peter Broqvist + Guests.

Can I get more information?

Yes, send an email to peter.broqvist@kemi.uu.se or just ask me when you see me. You can also ask Jolla Kullgren. 

How do I register?

Send an email to peter.broqvist@kemi.uu.se .

Best Regards

Peter Broqvist