Welcome — what this blog is for

I decided to start writing here for three reasons. None of them are “build an audience.”

The first is that my graduate students keep asking me questions in office hours that I’ve answered before — not because they weren’t listening, but because the answer lives in my head, and each student gets a slightly different version of it depending on the example in front of them. A blog is a way to write the answer down once, well, and point future students at it.

The second is that I do a lot of writing-adjacent thinking — margin notes, lecture prep scribbles, half-drafted grant-figure captions — that never becomes anything because nobody’s waiting for it. Giving it a home, even a loose one, means the thinking gets a little more rigorous. “Nobody cares” is not the same as “this doesn’t count.”

The third is that the field of statistics education is in an interesting moment. The ASA has said plainly that over-reliance on p-values is a problem. GAISE tells us to prioritize reasoning and intuition over procedure. Geoff Cumming has been shouting “effect sizes!” for twenty years and the field is finally starting to listen. I find myself with strong opinions about how to translate all of that into a one-semester graduate course, and strong opinions that aren’t written down tend to decay.

So — what to expect here:

• Teaching notes. Short posts when something clicks in class, or when I change my mind about how to teach a topic. These are the most frequent.
• Pedagogy reflections. Longer pieces when I have something worth saying about course design, assessment, or the tooling I build for my students (see ztchi.hgaladima.com).
• Research-in-progress. Occasionally, usually when I want to think out loud about a methodological puzzle I’m stuck on.
• Unpolished. That’s the point. Polished work goes in journals. This is where the thinking happens.

What you won’t find here: hot takes on Twitter discourse, AI doom-or-hype, or generic “here’s why statistics matters” essays. There are plenty of better places for all three.

Thanks for reading. If anything here is useful, let me know — especially if you’re teaching biostatistics to graduate students and want to compare notes.