Bayesian Data Analysis for Babies
A book on Bayesian data analysis for ages 0-99+. Illustrations by Nano Banana Pro, texts by Claude 4.5 Opus, prompts by Juho Ojala (@juhoojala). Juho works as CTO at the Upright Project.
This began as a joke, but I liked to results, so I made this available for others, as a free download and a paperback on Amazon.
The book and the descriptions in this repo are authentic AI-generated content ✨: no edits or iterations have been done after initial prompts, except for some technical edits to meet Amazon’s formatting requirements.
Description …
Bayesian Data Analysis for Babies
A book on Bayesian data analysis for ages 0-99+. Illustrations by Nano Banana Pro, texts by Claude 4.5 Opus, prompts by Juho Ojala (@juhoojala). Juho works as CTO at the Upright Project.
This began as a joke, but I liked to results, so I made this available for others, as a free download and a paperback on Amazon.
The book and the descriptions in this repo are authentic AI-generated content ✨: no edits or iterations have been done after initial prompts, except for some technical edits to meet Amazon’s formatting requirements.
Description ✨
Finally: a statistics book that starts where knowledge actually starts
Everything you know started as a guess that got refined.
Your first taste of food. Your first time being left alone. Your first encounter with a stranger. Each began with uncertainty—a prior—and each was shaped by evidence into something more definite. This is how knowledge works.
Babies do this visibly. They form priors, observe outcomes, update, repeat. Dozens of times before breakfast. They’re building models of the world from scratch, one data point at a time.
Bayesian Data Analysis For Babies is an illustrated field guide to this process. It names what babies already do: sequential updating when mom leaves and returns, likelihood estimation during bedtime negotiations, probability distributions when sniffing the air from the kitchen.
The goal isn’t to teach babies statistics. It’s to show the rest of us what learning looked like before we forgot to notice.
Written in gentle, bouncy rhyme and brought to life with warm illustrations, this book is for curious babies, nerdy parents, and anyone who’s ever wanted to explain conjugate priors using a high chair.
Inside the book
- 7 beautifully illustrated pages of Bayesian wisdom + 17 page isomorphic epilogue in the style of Douglas Hofstadler and Lewis Carroll (to meet Amazon’s minimum length requirements)
- Core concepts include priors, posteriors, likelihoods, probability distributions, sequential updating, etc.
- Friendly guide "Dr. Quack, PhD"—a rubber duck with glasses who offers technical footnotes for the grown-ups
Perfect for
- 🍼 Bayesian babies
- 📊 Data scientists expecting their first child
- 🎓 Graduate students who need a gentler explanation
- 😴 Parents who want bedtime reading that doesn’t insult their intelligence
- 🎁 People who don’t gift from the center of the distribution
What readers are saying
- "My baby grabbed this book over Goodnight Moon. I’ve never been prouder." — A.G., statistician & new dad
- "I’m a PhD candidate and this cleared up things my textbook couldn’t." — K.M., reviewed while crying
- "Gah." — Eleanor, 11 months
License
You are free to use the book (including print it out) for your personal use. No redistribution or commercial use without permission, but don’t hesitate to ask.