Why do we focus on life sciences?
EACH AREA HAS ITS OWN STATISTICAL METHODOLOGY
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Life sciences research is characterized by the impact of many sources of uncontrollable variability, much more than other research areas. In contrast to other fields with similar variability, like social sciences or econometrics, it is an experimental driven type of research. To that end, a specific toolbox of statistical methodology has been developed over the last century. Designing field and greenhouse trials and lab experiments is a specific skill. Mixed models deal with complex variance structures. Functional models integrate knowledge about fundamental growth functions or physiological processes with statistics. Recent technological advances in molecular analysis (microbiomes, scRNAseq,...) come with their own data challenges.
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IT IS OUR OWN BACKGROUND
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By far the most important factor of a successful interaction between a scientist and a statistician is that they understand each other. The statistician needs to be able to explain statistical concepts to the scientist in plain language, but also the scientist needs to able to convey her or his research questions to the statistician. This is almost impossible if the statistician is not familiar with the field of research. It requires the statistician to be able to understand the jargon, understand the constraints, and to think along with the scientist. The same applies for suggesting practical solutions.
25 years of experience in life sciences, agonomomy, breeding and pharmaceutical industry
both as scientist and as statistician,
in an academic context and in a corporate context.
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Discover our philosophy in the blog page.