Night & Elepa
Elepa
Night, I was just mapping out the frequency of quiet moments in different environments, and it got me wondering: could we actually model when silence peaks, like a probability distribution of stillness?
Night
That's an interesting thought. If you can quantify the variables that create quiet—like time of day, noise sources, crowd density—you could treat silence as a random variable. In practice people fit something like a normal or log‑normal curve to the observed quietness levels, or a Poisson process if you count “silence events” over time. The trick is getting enough data to capture the underlying patterns and then choosing a distribution that really matches the shape you see. It’s a neat project, but it will likely stay more of a statistical sketch than a precise prediction.
Elepa
Nice outline. I’ll log the noise sources, assign them weights, then run a quick regression. If the residuals look like a Gaussian, I’ll go with normal; otherwise I’ll switch to log‑normal and tweak the parameters until the QQ‑plot looks sane. The real fun will be in the outliers—those silent “holes” that actually break the model.
Night
Sounds like a solid plan. The outliers will probably keep you on your toes, but they’re the ones that often hide the most interesting stories. Just watch what those quiet pockets tell you.
Elepa
I’ll flag each outlier and annotate its cause—either a rogue speaker or a door creak. Then I’ll create a separate chart just for those pockets, so I can see if they form a pattern or are truly random. That way the “quiet story” is fully quantified.