Video of Analysis of "Patterns of Deployment of Toxic Covid Batches" (Toxic Batches Appear to be Systematically Released)
(www.bitchute.com)
🤢 These people are sick! 🤮
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It doesn't show coordination between the manufacturers at all. All it shows is buying patterns have changed over time. Rotating between suppliers for items which are mostly interchangeable is normal.
You don't have the full data regarding how big the batches are, who is buying them, when are they buying them, how much from each are they buying. Without the full data, you cannot draw any reliable conclusions.
For the data presented to be correct, it would have to have equal sized batches, that are distributed evenly, and simultaneously to hospitals, doctors, and clinics everywhere, from all manufacturers. That is surely not happening.
You have no way of knowing if it was consumed as quickly as it was made. It could have been damaged in transport, forgotten in a back room and thrown out, shipped off to another country, or a whole slew of other possibilities.
Seeing patterns in data is meaningless. If you cannot isolate away an exact cause for a particular pattern, you cannot draw a specific conclusion from the pattern.
I work with real data too. That's why I know about selection biases and similar issues. Most statistics are junk.
The VAERS system only covers 1% of actual cases, this is well known, not contrived. Most doctors don't even know what it is. Any statistics you try to draw from VAERS is going to slanted towards those who know about and use the system.
It also doesn't provide a full picture of anything you look at. If one batch is 10 times the size of the other, and the amount of adverse effects is 10 times the size of the other, then both batches are just as deadly and have the same percentage of adverse effects, although one of them is going to look 10 times worse, when it isn't.
Since the batch data is woefully incomplete in a variety of aspects, I have the luxury to tell you any conclusions drawn with it is pure fantasy.
I recommend reading "How to lie with statistics" and "Statistics done wrong".