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The knowledge about the bias variance trade off is very important for you as a statistician as it comes across your work – especially exploratory work – all the time. Taking care about it will help you avoid problems of over- or underfitting your models.  Wikipedia explains the principle very

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Interview with Jenny Devenport Jenny has encountered several highly competent people throughout her career who have admitted that they entered one path or another based on certain assumptions that were not entirely correct. Further, she has talked with interns about their future career interests and she sees them teetering on the

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Interview with Nancy Carpenter The COVID-19 pandemic has put pharmaceutical research firmly into the spotlight, with the urgent need to develop new therapies, tests, and vaccines. For those outside the industry, hearing announcements in the mainstream media, it is not always easy to understand the intensity of the work and

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Should we oversimplify statistics, or should managers learn more about statistics? If you’ve been working as a statistician for a while, you know that you have to keep it simple if you want managers to understand you. Of course, I speak about those managers not being statisticians themselves. There are a

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Interview with Swarna Khare Outside of statistics departments, we are often seen as tactical and operational implementers. This branding makes it hard for statisticians to be included in strategic discussions. This limits our ability to influence the organizations and projects. It can even lead to entire departments being outsourced or

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Interview with Paolo Eusebi Our job as statisticians focuses primarily on the analysis and communication of uncertainty in its many aspects. For this episode, I think of uncertainty as the variability in the population we are studying, the uncertainty around estimates, or the model uncertainty, which we might capture via

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Interview with Beth Manning What is change management? Is it only something for big corporate initiatives or does it also apply to smaller changes?Why does it require so much consideration?What’s hard about change? Change management is something I never thought about being interesting for statisticians, but recently, I needed to

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Interview with Nelson Knowledge sharing is close to my heart and Nelson, who is a very knowledgeable statistician, has shared a lot of articles in LinkedIn and on his website. Nelson has always been keen to learn from others and share that knowledge broadly, so we’ll be exploring similarities and differences

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I still can’t believe how fast things happened, and I am truly grateful for all of this. I interviewed a lot of people who have the same goal as mine – that is to build our expertise. I learned a lot and how important it is to know where the

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Part 2 Do you want to review a data visualization effectively? Do you want to provide your organization with a simple tool to improve your data visualizations? Do you need a checklist for yourself to make sure you covered everything for your data visualization? This episode is for you! Never

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Part 1 Do you want to review a data visualization effectively? Do you want to provide your organization with a simple tool to improve your data visualizations? Do you need a checklist for yourself to make sure you covered everything for your data visualization? This episode is for you! Never

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Interview with Björn Bornkamp and Kaspar Rufibach Principal stratification used to play a role only in observational research but at least since the addendum of the ICH E9 guideline, this approach to causal inference became a hot topic. In this episode, I talk with 2 experts from Novartis and Roche.

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