STATfags Call to dig.

A few nights ago, an Anon dropped the first graph noting the almost perfectly linear increase in posts over time from February 2018 until now. This generated a little discussion over the next two breads and like a lot of stuff, petered out. But remained a puzzling question, at least in my mind.

I've done a LOT of statistical modeling in the past and can tell you that virtually NOTHING done by humans follows perfectly linear trajectories without significant design influence and constant management…essentially removing the human-ness .

The Anon was quizzed (and if you're here, please jump in and take this..) and explained that it was simple grabbing of post numbers and I believe 10 day intervals from the archive breads. Then regressing that to a line for fit…and what a fit… r = .9966 With 1.0 being perfect…this is machine precision and considering what goes on here, big machine and tight controls.

So, I decided to take a proxy and check the fit, and took Q posts from the dates closest to the first and middle of the months from February 2018 until this week (post numbers are jacked before that due to migration). Some of the dates are close because there weren't any posts, or any on /qr/ so I took the closest. I doesn't matter, the spreadsheet accounts for the intervals in dates for the fit.

What was my fit? r = .997 Essentially validating the earlier spoopy findings. I'm not stealing thunder…this was just a confirmation of the other Anon's work. All credit goes to their callout.

What could be behind this? Are WE already in the matrix? Think about the stock market as a proxy for variability. It is variable at all levels of granularity… /qresearch/ seems only to have variability at modest granularity and finer.

This is seriously spoopy and I'd like to hear some thoughts and have some better statfags look at the more granular data, because the metadata looks like machine management.