Welcome to a brand-new year and an exciting new episode of The Effective Statistician!
I’m thrilled to kick off 2025 by sharing some incredible news—I’ve written a book! After years of planning, false starts, and a lot of learning along the way, How to Be an Effective Statistician is finally complete and will officially launch on January 15th. In this episode, I take you behind the scenes of how the book came to life. I’ll share why I wrote it, how it’s structured, and the practical insights it offers for statisticians, data scientists, and other quantitative professionals.
Whether you’re looking to improve communication, manage challenges, or simply be more effective in your role, this book was designed with you in mind. I’ll also give you all the details about the book launch party, where we’ll celebrate, learn, and connect.
Join me as I reflect on this journey and what it means for our community!
Key points
- New Year Episode
- Book Announcement
- Personal Journey
- Target Audience
- Content Overview
- Fictional Narrative
- Chapter Structure
- Book Format
- Launch Party
- Ordering Info
Don’t miss this inspiring episode of The Effective Statistician! Whether you’re curious about the process of writing a book, looking for actionable career insights, or simply eager to learn more about How to Be an Effective Statistician, this conversation has something for you.
Tune in now to hear the full story behind the book, and be sure to share this episode with your friends and colleagues. Let’s work together to empower statisticians and other quantitative professionals to make a greater impact in their fields!
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Transcript
Behind the Pages: How I Wrote ‘How to Be an Effective Statistician’
Alexander: [00:00:00] Welcome to a new episode of the Effective Statistician. This is the first episode that is going to publish, or as you listen to it, got published in 2025. And it’s the first episode that I’m recording since a very long time. All the Episodes that have been published in the last two, three months have been recorded much earlier because of medical leave.
I was not able to record a lot of podcast episodes. This is the first one since a couple of months. And I have some pretty amazing news for you. I’ve written a book. And I’m pretty Astonished about it because it took me several years to get started with the book or let’s say it’s that way. I started a couple of times and never moved really forward [00:01:00] with it.
But now it’s done. And it will become available on January 15th. You can already pre order the book kindle version, so the ebook, and on January 15th, you can also order the paperback and the hardcover book. One thing on January 15th, I will also have a launch date party. If you are Listening to this before January 15th, head over to the effective statistician and register for the launch date party.
Why did I actually write the book? Of course, my podcast is my primary way of communicating with the community. But I think lots of people just want to read something. And therefore for those that really enjoy [00:02:00] reading and have everything in one place, I wrote this book. And I wrote it as if I would like to have had it at the beginning of my career, maybe 20 years ago.
And I think I got there because a couple of people Whom I’ve sent a preprint, told me exactly that. They would have loved to have had that book 20 years ago, at the start of their career. Because then they would have had much less pain, much less problems, much less challenges. And I’m pretty proud that I reached that.
Now, this book is a very practical, hands on book. There’s, by the way, no statistical theory in it. It is all about being effective as a statistician. It’s about good communication skills. It’s about [00:03:00] negotiation. It’s about fighting overwhelm. And it is written in a way that I hope is really easy for you to connect to.
Each chapter stands more or less on its own and has a story about a fictional character called Claire. Claire is a statistician and could be a programmer, or an epidemiologist, or any other kind of person. I have the stories rather generic in that type. End. That character, my hero, so to say, of the book, faces all the typical challenges that statistician, epidemiologists, data scientists will face in medical research.
They need to work with a team, they need to convince people, they have a supervisor that they need to work with, and Claire has one big [00:04:00] advantage. Claire has a mentor. called Walt and she learns a lot from the mentor Walt. Of course, don’t take everything as it would really happen because Walt has actually a lot of time for Claire.
He’s probably not doing a lot of other things. But you will learn a lot from the experiences Claire has and then the reflections with Walt. There are stories that also include The feelings of Claire. When she’s anxious. What she fears. What she’s ashamed about. What she What makes her frustrated.
And this is based on things that I have heard from the community again and again. What frustrates them? And I have written it in such a way. She also meets the typical kind of characters that you will meet. People that are easy to convince, and people that are [00:05:00] hard to convince. People that are very much driven by, maybe their peer recognitions, others that are driven by, financial aspects, timelines, whatsoever.
So she works with people in regulatory and medical affairs and the clinical people. She has stuff to outsource, all these kind of different things. Every chapter has a summary, so that You can, go back to the chapter and get easy access to the key learnings from the chapter. And it also has a couple of practical exercises or things you can apply in your day to day job.
So that you can transform what you have learned into action and outcomes for you. That was really [00:06:00] important for me. Now, if you want to dive deeper into a couple of these concepts, I also have QR codes in the book, so that you can jump to podcast episodes that go into some of the concepts in the book in more depth.
As I said, this book is not a statistics book. It is for statisticians, data scientists, epidemiologists, programmers, and other quantitative scientists. And it has no formulas in it. Also, it is not a kind of this typical textbook, as I said. And it’s not, of course, having all the tips that I have on the podcast and all the tips that I have in my trainings because that would probably be too much for the book.
And I’m already thinking about a second volume of this [00:07:00] book. This book is also specifically for individual contributors. So it of course has lots of leadership experts leadership advice in it. And I’m sure supervisors, team leaders, will benefit a lot from it as well. But you don’t need to have, direct reports to read this book.
I’ve written it in such a way that you will benefit from really working with it and Please join the book launch party on January 15th because there I will tell you more about the book. We will have a training on how to be an effective statistician. We will have a panel discussion with Gary Sullivan and some surprise guests.
And so That will be a great moment for me to celebrate that this book is [00:08:00] finally available. And if you want to order it, just go to Amazon, search for Data Scientist and Schacht, my last name, S C H A C H T, Data Scientist, Schacht, S C H A C H T, and then you can find my book, hopefully on the first page.
That will also, by the way, tell the algorithm that data scientist and, which is a pretty crowded search term, and this book is quite well connected and that will help others in the community find this book. Thanks so much for listening to this first episode of the year. I wish you an absolutely wonderful start into 2025.
And I’m so stoked about the book and working together with you so that we really help statisticians have a bigger influence in the industry. [00:09:00] See you soon.
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This group was set up to help each other to become more effective statisticians. We’ll run challenges in this group, e.g. around writing abstracts for conferences or other projects. I’ll also post into this group further content.
I want to help the community of statisticians, data scientists, programmers and other quantitative scientists to be more influential, innovative, and effective. I believe that as a community we can help our research, our regulatory and payer systems, and ultimately physicians and patients take better decisions based on better evidence.
I work to achieve a future in which everyone can access the right evidence in the right format at the right time to make sound decisions.
When my kids are sick, I want to have good evidence to discuss with the physician about the different therapy choices.
When my mother is sick, I want her to understand the evidence and being able to understand it.
When I get sick, I want to find evidence that I can trust and that helps me to have meaningful discussions with my healthcare professionals.
I want to live in a world, where the media reports correctly about medical evidence and in which society distinguishes between fake evidence and real evidence.
Let’s work together to achieve this.
