New Chapter, New Coupon, New Sneak Peek, New Code Notebooks

Dear Causal Inference in Statistics Enthusiast,

[COURSE] Introduction to Biostatistics — Exclusive Coupon Code

We finally did it: all the material to the online course is recorded. We are editing the content and preparing the user experience on the platform.

Expect a release in February 2026 🎉

To celebrate this important milestone, Aleksander Molak and I sat down for a discussion. He asked me the one thing I want students to take away from the Intro to Biostats online course. My answer:

We decided to take the celebration even further by offering a 36$ discount until Monday, Dec 1, 23:59 UTC. The price will never be lower.

What's The Plan?

• [BOOK] Chapters 1,2, 3, and 5 Now Available

• [PODCAST] Live Events For 2026

• [PODCAST] Sneak-Peak On My Book Writing Process

• [CODE NOTEBOOK] Use Robust Estimation Procedures

• [BOOK] An Overlooked Causal Inference Masterpiece …

• [COMMUNITY] Collaborators

• [CONSULTING] Training and Workshops

• [FREE] Resources You Might Like

[BOOK] Chapters 1,2, 3, and 5 Now Available

To those who preordered: Chapters 1, 2, 3 are now supplemented with Chapter 5 —The Art of Observational Studies: Pragmatically Bridging Causal Frameworks!

• This 55-page monster chapter includes a case-study code notebook, dozens of thoughtful exercises, guidelines and frameworks for conducting observational studies, and discussions about target-trial emulation, negative controls, well-defined interventions, and more.

If you pre-order my Causal Inference in Statistics, with Exercises, Practice Projects, and R/Python Code Notebooks, you now receive:

• A 230 page PDF with the 4 chapters

• An online version with the 4 chapters (see video below)

• 6 R code notebooks

• Receive the new parts of the book upon release (2 new chapters + 5 additional notebooks, coming soon) and any updates to the material via Github

• A pre-order for the physical book once it is complete

In case you missed it, a preview of the online version:

You can order now—you will be the first to receive the new material when it launches 😋 

[PODCAST] Live Events For 2026

I’ve done many live events over the year, all available on Youtube. I’m kicking off 2026 with an exciting guest to be announced soon.

Any guests you would love to see? Let your imagination run wild, and let me know!

[PODCAST] Sneak-Peak On My Book Writing Process

Ever wonder how writing a technical book feels like? I lift the curtain on this life-changing experience in Dr. Alexander Schacht’s podcast The Effective Statistician

[CODE NOTEBOOK] Use Robust Estimation Procedures

Dont’t test your assumptions: use robust procedures, clever study design, and sensitivity analysis to make your assumptions credible.

I wrote a blog post about Welch’s t-test, including a tutorial, a simulation study, and a free code notebook.

[BOOK] An Overlooked Causal Inference Masterpiece 

Shadish, Cook, and Campbell - the latter having pioneered the Regression Discontinuity Design (RDD) in the 1960s, a quasi-experimental approach that revolutionized field research in social science - present their conceptual theory of generalized causal inference.

This book has close to 0 math and barely any formal statistics, being instead replete with real-world examples drawn from social sciences and policy research literatures, and deep, incisive insights into scientific research methodology.

Amongst other groundbreaking concepts, I particularly appreciated their typology of validity, which goes beyond the internal validity-external validity dichotomy for inference, but instead extends validity to also encompass statistical conclusion validity and construct validity, which are particularly important in biomedical and social sciences.

My favorite passage from the book is: "Validity is a property of inferences. It is not a property of designs or methods, for the same design may contribute to more of less valid inferences under different circumstances."

I incorporate insights from this masterpiece in Chapter 7 of my own Causal Inference in Statistics, which covers quasi-experimental designs.

I’m releasing Chapter 7 next.

[COMMUNITY] Collaborators

The Biostatistics Group is looking for new collaborators for 2026.

What’s in it for you? 

• You showcase your expertise, including a short author profile and a link of your choice.

• Our website gets 1k+ clicks a month—this is a great way to drive traffic to a link of your choice

[CONSULTING] Training and Workshops

You may already know that I’m a University Lecturer and that my passion is teaching 💜 

I offer training and workshops in causal inference, real-world evidence, and biostatistics.

I’ve trained

• Pharma RWE teams

• Industry scientists in biotech

• Research Labs

• And more!

My approach is engaging, warm, and thorough.

I’m almost fully-booked, but could take on an additional workshop or training.

[FREE] Resources You Might Like