 Earlier this week, some statistics were shared regarding the likelihood and probability of Q and Donald Trump posting within mere milliseconds of each other repeatedly.

An anon obtained and shared a list of the times of all Q posts from qanon.pub, and all Trump’s tweets from trumptwitterarchive.com. They created a CSV file listing all these events, and posted that file to Pastebin so we could work with the raw data, too.

Zero deltas where Q posts first are most interesting, because this sequence eliminates the possibility of zero deltas arising from someone watching for Trump tweets and then posting in response. If there’s a spike at zero delta when Q posts first, that’s evidence of Trump choosing when to tweet based on the timing of Q’s posts.

Each Q post is measured against the number of seconds between the Q post and the next Trump tweet. The statistician then put these in one-minute bins (zero delta = Trump tweeted within 60 seconds) and graphed the results:

The number of “zero delta” events (27) is higher than for any other delta on the graph. This is statistical evidence that Q is not a LARP. If Q were a LARP, you would expect to see random noise in this graph.

For simplicity’s sake, let’s assume that POTUS tweets 10 times per day, at roughly 1 post per hour, in a 10 hour window.

In other words:

Your chance of posting 1 minute before Trump is 1 in 60 or 1.67% chance.

Your chance of posting 20 seconds before Trump is 20 in 3600 or 0.54% chance.

Your chance of posting 10 seconds before Trump is 10 in 3600 or 0.27% chance.

What about multiple times in a row? Just multiply the values together:

Two times in a row at 1 minute before? 1/60 * 1/60 or 0.027% chance.

Two times in a row at 10 seconds before? 10/3600 * 10/3600 or 0.00077% chance.

Three times in a row at 1 minute before? 0.00046% chance.

Three times in a row at 10 seconds before? 0.0000021% chance.

If you factory workers or engineers are familiar with 6 sigma process, 6 sigma is used to ensure no defects ever occur. 6sigma is equal to 99.99966%, which assumes success in all conditions → That means, the chance of failure (to be considered success) is less than 0.00033%

In other words, it only takes a few times in a row to make it statistically impossible to be a coincidence.