---
title: Central Limit Theorem Explained
date: 2025-11-07T00:00:00
author: Charlie M.
category: SIGNAL
---
I was sitting on my balcony this morning, trying to soak in some sunlight and maybe wake up my brain a bit. It’s kind of my new ritual, you know? I read somewhere that morning sunlight helps with serotonin or something. But then I scrolled through Instagram instead and got distracted by videos of cats playing piano. So much for wellness, right?
Anyway, I was thinking about this thing called the Central Limit Theorem. I’ve tried to wrap my head around it before, in those moments when I’m pretending to understand statistics. It’s one of those concepts that seems important but also...confusing? Like, I get the gist: when you have a lot of weird individual data points, they somehow end up looking like a normal curve when you put them all together. At least, I think that's the idea. Something about averages and bell curves, maybe?
I started thinking about how many times I’ve tried to apply this, like when I was tracking my workouts. I thought if I just logged enough running times, I'd see some kind of pattern. But honestly, it felt more like chaos theory than anything else. One week I’d feel like I was flying, and the next I’d question whether my shoes were made of lead. Were my results ever really “normal”?
Then there’s this thing about sample size. Supposedly, if you take enough samples, even if they’re all different, they’ll average out to something predictable. But I get lost right around there. How many samples are enough? How does randomness become predictability? It feels like magic or a bad joke.
I read somewhere, I think it was in a textbook from college, that the theorem holds regardless of the shape of the original data distribution. Didn’t make much sense to me then and kind of feels the same now. Like, are we really saying that everything in life eventually just smooths out? Feels overly optimistic. I can’t even get my phone's autocorrect to smooth out.
The whole thing is supposed to be this backbone of statistics or something. Maybe it works for data, but what about life stuff? Relationships, decisions. Can you really just average things out and expect a neat middle point? Because, honestly, things rarely feel normal, you know?
I guess I'm trying to understand it in the way you try to understand people you meet at parties, where no one is who they seem. Like you just need to learn enough about them to nod and smile but never quite feel like you grasp the whole picture. Maybe that’s the Central Limit Theorem for me. Something I'm only pretending to get while I wait for my coffee to kick in and my Instagram feed to load another cat video.
And maybe that’s okay. Or not. I don’t really know.