Afraid of speaking up?
Afraid of talking to senior management?
Afraid of giving a presentation? 
Afraid of speaking to someone new?

Then you are definitively not alone. Many supervisor worry about their staff not speaking up and I have come across even senior statisticians, who are very uncomfortable about doing a pre-recorded interview for the podcast.

How do you create and teach effective and moving content that your audience will pay attention to and add great value to them?

Teaching is really important to us statisticians because we need to explain stats and data all the time to our colleagues, within stats or outside stats.

Is having a mentor really beneficial?
What is Manatee Mentor?
What are its key features?
How can this predict your professional success?

Manatee Mentor is an AI-powered platform to make mentoring inclusive, affordable and accessible to all. It can match or unmatch with your mentor and mentee through its constantly learning AI algorithm. You can choose your topic of mentoring, preferences, and find your perfect match in few clicks.

What is the data project?
Why are data management programs a strategic imperative?
Why do they fail?

Usually a data management project starts with a change of perspective in the organisation, especially from senior leaders. To make such a project happen, data leaders must be familiar with the principles of change management, learn to speak the language of business, and be excellent listeners to craft and communicate an interesting and realistic vision to release value from information.

You may think that QR codes aren't new. But it's actually quite something new in our field.

We as statisticians, should not just leave the use of QR code to other functions such as medical writing. Instead, let's leverage this tool to have an impact and improve our output.

Today, we have a special guest, Shanti. Learn while she shares with us her vast experience in the pharmaceutical industry collected over 25 years. She held various positions inside and outside of statistics organization.

When I started my career as a statistician in the clinical world, I was wondering about safety analysis. I thought it's always the same - count the patients with an event - job done! Then just repeat.

But it's not that simple, especially in more complex situation where you have different follow-up times. Then the patients that stay longer on treatment as they benefit from it, also get more adverse events. Naively counting the patients with events or the number of events may make the beneficial treatment look worse. So, how can you account for this?

Why spend part of your career in non-clinical statistics?
What are the advantages?
What is the importance of having a variety of tools?