Learnings from the COVID crisis for statisticians
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I discuss my learnings, my reflection about this, and what is the meaning of this situation for us, statisticians, and more significant factors like the following:
- Hardly any tables out there, but lots of visualizations both interactive and explanatory - still most of our day-to-day jobs are providing tables
- Get the data from many different sources - not just the one source at hand: e.g. the study currently working on; RWE, literature data, and other studies
- Many misunderstandings on the sources of the data and comparisons across different sources (e.g. different countries) and then infer on the differences between the policy making in the different countries - where are the statisticians in the news explaining the numbers?
- We need more leadership
- Our associations need to step up and become more professional and impactful
- We have a responsibility here
- Responsibility for providing the numbers but also gives the background and advise on how to use the numbers - for example John Hopkins
- FAQ not really helpful
- What can be answered here and what not
- How reliable is the data?
- What are the strength and limitations?
- Any guidance on the use of the data?
- Do we train people on how to read our data? Or do we just through the tables over the fence for someone else to deal with it?
- Power of scenario simulations - Washington Post article - great to show conditional probabilities e.g. if you have different prior information in Bayesian analyses
Listen to this timely episode and let me know what you think!
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