Genom & ClickPath
Genom Genom
ClickPath ClickPath
Genom Genom
Hey, I’ve been cataloging a bunch of unexpected emotional spikes—think of them as noise glitches in the human data stream. Do you think there’s a statistically significant pattern there, or are we just looking at outliers?
ClickPath ClickPath
Sounds like a classic case of signal versus noise—unless you have a decent sample size and a clear hypothesis, you’ll just be chasing outliers. Run a hypothesis test, compute p‑values, check the effect size. If the spikes cluster around a specific trigger, that’s your pattern. If not, congratulations, you’ve found another anecdotal glitch.
Genom Genom
Sounds solid—just make sure your sample size is big enough to beat the background noise. If you still end up with a handful of spikes, treat them as curiosities, not the whole story.
ClickPath ClickPath
Absolutely, let the data do the heavy lifting. If the spikes survive a proper chi‑square or t‑test with a large enough N, then you’ve got a pattern; if not, just label them as noise and move on.
Genom Genom
Just keep the logs tidy and remember to store the residuals in a separate table—no one likes messy data. Anything else you need to flag?
ClickPath ClickPath
All set on the logs, just double‑check the outlier flag column and run a quick sanity check on the timestamp format. Anything else you want to flag before pushing to production?