Improving Your Statistical Questions
Daniël Lakens, TUEindhoven, The Netherlands
When proposing alternatives to p-values statisticians in the scientific literature often commit the ‘Statistician’s Fallacy’, where they declare which statistic people really ‘want to know’. Instead of telling others what they want to know, statisticians should teach people which questions they can ask. All statistics have assumptions and practical limitations. I will discuss the ways p-values have been criticized as an illustration of the rather unproductive approach of dismissing one approach to statistical inferences, instead of improving the way it is used in practice. As long as null-hypothesis tests have been criticized, researchers have suggested to include minimal-effects tests and equivalence tests in our statistical toolbox. Although these types of tests have the potential to greatly improve the questions researchers ask, they are rarely taught to people who are expected to use statistics in the future. By more formally explaining what questions are answered by different approaches to statistical questions, we can help people to improve the statistical questions they ask.
A stat’s life at GSK
Sylvie Scolas, CMC Statistical Science, Rixensart, Belgium
My talk will focus on 3 parts. I will first explain my personal experience before working in a big pharma company: what did I study and how did I end up there. Secondly, I will shortly give an introduction of the company itself: GSK; and try to explain the different statistical teams in such a big company. Thirdly, I will try to illustrate my current job with some examples.