We all know how to specify a table and our processes support this. However, designing an awesome data visualization does not work this way. Our approach to table specification does not work?

As statisticians, we are one of the most capable professionals to understand and to relay the right information to the general public about the most talked-about situation - the Corona Virus.

In today's episode, I want to express what's on my mind and on my heart about this topic. You can agree or disagree with this and let me know what you think about it.

I also discussed my learnings, my reflection about this, and what is the meaning of this situation for us, statisticians.

Are you curious about how working from home works?
How can you know if this is for you?
What are the advantages and disadvantages when working from home?
What is a good set-up when having a home office?

The COVID-19 outbreak forces many of us to work from home. But even before this, working from home became a growing trend, most especially at the moment. This interview will help you understand if this is something for you or not, and how you can make it happen, have fun with it, and get a better balance of your working time and other things.

Why is visualization so important?
How do you determine the goal of visualization?
What is the big difference between explanatory visualization and exploratory visualization?

Who is Florence Nightingale and what is impressive about her?
Why would it be interesting to talk about her at the upcoming PSI conference? She’s famous for her visualization – what could statisticians today learn from her about visualization?

Listen now to learn more!

After a career that brought you as a statistician to various parts of the pharma world, what is the new job, that you just took on about?

What are the unique skills of statisticians - beyond just knowing about stats - compared to many other functions in the pharma world?

Which problems do statisticians need to take care of beyond the current regular work?

How can we make time to tackle these problems?

What skills do statisticians need to improve on to successfully tackle these problems?

Do you effectively communicate complex data?
How can visualization help you when you are
. . . analyzing data?
. . . reporting data?
What initiatives and groups work on this topic and will help you?

Real world evidence (RWE)
Big data
Real world data (RWD)
Pragmatic studies

There are lots of buzzwords floating around and especially with the FDA having a bigger focus on RWE. Many teams in the different pharma organizations concentrate on this type of evidence.

Do you know what your external profile is?
Do you have an idea of how to improve it?

In today's episode, Liz Cole and I will dive deep into a topic called content marketing. It’s kind of meta, since this podcast itself originates on these ideas. Does this sound frightening or disturbing? It shouldn’t.

With so many recent advances in AI, it is important for statisticians to both keep up to date with the most recent methods and getting involved in guiding their application to the most pressing statistical challenges.

In today's episode, Karim and I cover cutting edge examples of how data science and statistical sciences are intersecting. Learn from this episode why different approaches matter when looking at clinical development data.