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Not every application leads to a new method and many years of problem solving sometimes result in generalizable expertise.We call that the statistical method, which is an important component of our research.
" and look up to a very small and select group of Statisticians for inspiration.
In the same time we are facing a raging data revolution that could have provided inspiration, open up completely new areas of research, and placed our discipline at the core of our data-centric information society.
Our approach to research is "problem forward", as we start with and focus on the scientific problem.
This is in contrast with a "methods backward" approach, which would start with a method or theory and look for data sets and problems.
As its name implies, this model is the road map to follow to solve problems. a) When the process isn't doing what it is supposed to and people don't know why.
b) When things keep going wrong no matter how hard everyone tries.
And it is often a solution that is short-lived or creates numerous other problems within the organization.
The Problem Solving Model provides you a road map to continuous improvement.
Instead, an ever smaller number of statisticians work directly on emerging problems, new data structures, and data.
The problem is fundamental and obvious: there are very few statisticians working on data because the academic reward system and job market favor theoretical statistics. On this webpage we have tried to provide details about our research groups's solution for the future.