In this episode, I’m once again joined by Daniel Sabanés Bové for a deep dive into one of the most impactful tools for statisticians working with data visualization—R-Shiny.

We explore how interactive data visualizations can help you iterate faster, collaborate better across functions, and focus more on the actual scientific questions rather than just coding. Daniel shares some excellent examples from clinical trials and gives practical tips on how to avoid common pitfalls when building Shiny apps.

Whether you're designing your first app or maintaining a more complex one, you'll find plenty of value in this conversation—from best practices around UI/UX design to strategies for modular development and testing.

In this episode, I’m sharing three personal stories where soft skills—or better yet, human skills—made a huge difference in my work as a statistician.

Whether it was building trust to access critical data, presenting results in a way that truly resonated, or negotiating a fair contract, these experiences reminded me how essential these skills are alongside our technical expertise.

In this episode, I’m joined once again by Daniel Sabanés Bové to talk all about R packages—why they’re so useful, when to create one, and how to do it effectively. Whether you’re just starting out with writing reusable functions or thinking about building a more robust and reusable R package, you’ll find plenty of hands-on advice in our discussion.

Daniel shares his experiences from working at Roche, Google, and now through his consultancy, Arconis. We dive into everything from writing clean and consistent code, to testing, documenting, and even promoting your package in the open-source world.

What You’ll Learn in This Episode:

In this episode, I welcome back Necdet Gunsoy, who’s now in a new role as the founder of EviMed, a boutique consultancy specializing in health economics, outcomes research, real-world evidence, and market access.

We dive into the often tense relationship between statisticians and market access professionals, exploring why these functions struggle to collaborate and, more importantly, how we can work together more effectively.

In this episode of The Effective Statistician podcast, I dive into the art of persuasion. As statisticians and data scientists, we often rely on logic and data, but true influence requires more than just being right.

Drawing from ancient Greek philosophy, I explore the three pillars of persuasion—ethos (credibility), logos (logic), and pathos (emotion)—and share practical strategies to help you effectively convince others.

Whether you are presenting new methodologies, influencing key stakeholders, or advocating for change, this episode will equip you with essential communication skills to make a lasting impact.

In this episode of The Effective Statistician, I sit down with Kaspar Rufibach to tackle a topic that affects statisticians every day—how to interpret p-values, confidence intervals, and statistical hypotheses.

We explore the differences between Fisher’s and Neyman-Pearson’s approaches, clear up common misconceptions, and discuss how misinterpreting statistical significance can lead to flawed conclusions.

Using real-world examples from clinical trials and drug development, we highlight best practices for communicating statistical results effectively.

Whether you're working with clinicians or business stakeholders, this episode will help you gain clarity on these fundamental statistical concepts and use them correctly in your daily work.

In this episode of The Effective Statistician, I dive into a crucial skill—building influence within a clinical trial team. As statisticians, we often need to negotiate timelines, advocate for better analysis methods, and ensure clear communication across teams. The stronger our influence, the more impact we can have on study outcomes and, ultimately, patients.

I break down the key pillars of trust—care, character, and competence—and share practical strategies to help you collaborate effectively, align team priorities, and proactively tackle challenges.

Tune in and start building your influence today!

I know firsthand how challenging it can be to manage a heavy workload while maintaining mental well-being. In this episode of The Effective Statistician, I talk with Peter Wehmeier about the five key dimensions of self-management—building strong relationships, setting priorities, making decisions, and taking action.

We share practical strategies to reduce stress, strengthen resilience, and take control of both work and life. With insights from Peter’s upcoming workshops, this conversation offers valuable tools to help you stay balanced and productive.

Tune in to learn how to take charge of your future!

Welcome to another episode of The Effective Statistician! Today, I sit down with Darko Medin to explore how artificial intelligence is transforming biostatistics.

Darko works as a biostatistician for companies worldwide and builds digital solutions that push AI’s boundaries. We dive into Bio AI Works, the platform he’s developing to improve AI reliability and eliminate issues like hallucinations in large language models. Darko explains how AI can enhance statistical accuracy, uncover hidden data patterns, and accelerate breakthroughs in oncology and precision medicine.

If you want to understand how AI can revolutionize biostatistics while maintaining scientific rigor, this episode is for you. Let’s get started!