This was the spreadsheet that Candace claims is the bombshell material of all the coincidences of the Egyptian plane crossing over Erika’s. When you actually look at it and break it down HONESTLY this is the conclusion:
This number doesn’t mean what you think it means.
If you want to talk about probability, you need (at minimum):
1. A complete flight log for both Egyptian planes
2. A complete travel log for Erika
3. A precise definition of “intersection”
4. A model describing what “random” travel looks like
5. The total number of non-intersections
6. Exact time windows (same hour? same day? ±3 days? same state?)
None of that is provided in your spreadsheet or in Grok’s answer.
You’re feeding Grok a pre-filtered list of 72 “hits” and then asking it the probability of those 72 filtered events being “hits.”
This is pure post-hoc reasoning. It's not data science or anything even close to it.
Here are the basic problems:
1. “Intersecting” = being in the same state within ±3 days.
A 7-day window + state-level matching is so loose that dozens of overlaps are expected for two parties who both travel in the same handful of states (AZ, UT, KS, MO, NE, DE).
This is not “tracking.”
2. You did not include all flights.
If you don’t show the planes’ full itineraries, the overlap rate is impossible to evaluate.
Cherry-picking the “hits” and hiding the “misses” invalidates every probability calculation.
3. You didn’t include all of Erika’s travel.
If Erika traveled 150+ times in 44 months, and only ~70 of those have loose state-level ±3-day overlap, the “probability” becomes trivial, not shocking.
4. Timing is ignored.
If Erika was in Missouri on the 10th and the plane landed on the 13th, you count that as an ‘intersection’ even if she was already gone.
Without in/out timestamps, you cannot call these “crossings.” Period.
5. Without full data, the “daily coincidence probability” is meaningless.
A real model requires knowing the total number of opportunities for overlap.
You provided only the successes.
That’s like listing every time you won at roulette and asking an AI: “What’s the probability I win this often?”
The answer is guaranteed to look spooky because you removed the losing spins.
6. The burden of proof is on the person claiming a clandestine foreign intelligence operation.
Not on everyone else to accept state-level, ±3-day coincidences as evidence.
The short version:
Your dataset is incomplete, your overlap definition is too fuzzy to have statistical meaning, your misses are hidden, your timeline doesn't include actual temporal overlap, and the model Grok used is based entirely on the cherry-picked subset you fed it.
The probability claim collapses the moment you try to formalize it.
If you want to do real statistics, publish:
- Full flight logs (every arrival/departure)
- Erika's full travel logs
- Exact timestamps
- A precise definition of “intersection”
- All the places where there was no overlap
Until then, “random coincidence is not credible” isn’t a conclusion. This is conspiracy propaganda.
https://x.com/ehnonamoose/status/1990637382534836523?s=46&t=aNrhKlmnaUDWMHyDnf-NZw
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