Do you have a great idea you want to move forward and you need others to buy in?

Maybe you want to improve a process or implement a new analysis approach. Your business partner might be your study team or your supervisor.

Whenever, we want to change something, we usually need others to agree into the next steps.

Aiden has first worked on simulations during studying statistics to understand which sample sizes lead to sufficient performance of statistics, which are only asymptotically normal. It helped him in many situations, in which it was difficult to tackle a problem analytically. Simulations help us understand very complex situations, and the development of new treatments is surely a very complex topic.

We designed this program for statisticians and data scientist to strengthen your leadership skills so you can maximize your impact at work even if you don’t have direct reports.
The Effective Statistician Leadership Program, a modular program of self-learning parts and moderated small group discussions, helps all statisticians and data scientists. It especially takes into account the needs of pharmaceutical statisticians, but the concepts will apply to any data scientist.
It aims at all levels of statisticians and helps both junior statisticians without management responsibilities and experienced statisticians leading teams. We believe all data scientists and statisticians can be leaders.

Check out and learn more about the leadership program here: https://theeffectivestatistician.com/the-effective-statistician-leadership-program/

Clubhouse is a new social media platform that is audio only and only works on iOS or iPhones for now, but it will be available for Android phones in 5 months.

Just like in any other social media platform, you can also grow your network here and speak with each other.

You can only join a Clubhouse room if you receive an invitation. So, head over to LinkedIn and follow me to get the notification posts and create a LinkedIn post telling that you want to take part in the Clubhouse event and tag me.

The room will be open on a weekly basis at 3pm CET to talk about the latest podcast episodes and how to be an effective statistician and data scientist.

See you there!

Do you sometimes feel that you disrupt your own happiness and success?
Are you overworked to make sense of yourself?
Do your emotions often control you?

Stuart and I got a recommendation to read a book entitled "The Chimp Paradox: The Acclaimed Mind Management". This book is an incredibly powerful mind management model that can help you become a happy, confident, healthier, and more successful person.

In today's episode, we're talking with a niche part of clinical research many statisticians never get actively involved in: DMCs.

David Kerr comes with a deep knowledge and long experience in this setting. We'll speak about:

What is a DMC?
What is the role of a DMC statistician?
What are the best skills and traits of the DMC statistician

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.

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 edges of some same fallacies. It’s all fun and science until you have to get a job. As you will make this decision at some point, Jenny wants to give you a few key points to consider when evaluating potential statistics / data science careers in drug development and healthcare.

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 collaboration that fuels game-changing new developments.

However, we know that there are thousands of ‘unsung heroes’ around the world, working in different capacities on different clinical trials to make the breakthrough. It has been a herculean collective effort.

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 lot of ways to explain statistical concepts to them, but this adds time to the presentation. Sometimes there won't even be a presentation, and all you have is sending the report via email.

From reading, from my experience, and from talking to other experienced statisticians, I have distilled the knowledge about this challenge into 5 steps.