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To: Q

The White House
@WhiteHouse

“I am pleased to announce that Mr. Stephen Miller, the current Deputy Chief of Staff of the Trump Administration, and one of my most trusted advisors, will become the Chief of Staff starting Monday, November 9, 2026. Susie Wiles, who has done an outstanding job, will be moving over to the Trump Political Operation. I want to thank her for her service as Chief of Staff — She has done a great job!” - President Donald J. Trump 🇺🇸

(Sorry Mr.President, but Wiles is a rat who gave you awful advise, like NOT touting your success at the border. 🙄)


893 posted on 11/06/2026 11:27:15 AM PST by TheConservativeParty ( )
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To: All; Election


I asked Grok what the chances were of 90% of Texas counties flipping from red to blue in 1.5 years were, leaving 6 months for people to start deciding from inauguration day.

This was the response.

One noventrigintacentillion. **

That's a 1 (one), followed by 420 zeros. 420 zeros. Even accounting for "muh vote turnout", this cannot be defeated. The number would still dwarf your chances for winning the PowerBall.

Wake up, America. You just got roofied, råped, and had a kidney stolen.









**The math checks out; the probability is correctly on the order of \(10^{-420}\).**

- Texas has 254 counties (confirmed).
- \(0.9 \times 254 = 228.6 \approx 229\) (correct).
- Recent national flip rate of ~86 counties out of ~3111 matchable ones (2020–2024 data) is \(\approx 0.0276\) per 4-year cycle. Scaling linearly to 1.5 years gives \(\approx 0.01035\) (approximate but as stated).
- Binomial model: \(X \sim \text{Binomial}(n=254, p=0.01035)\).
Expected value \(\mu \approx 2.63\).
\(\log_{10} P(X=229) \approx -420.3\), so \(P(X \ge 229) \approx 10^{-420}\) (order of magnitude correct; cumulative is dominated by the first term).

“Approximately 1 in \(10^{420}\) chances” and the English name for that power of ten are consistent with the calculation.

**Caveats (model assumptions, not arithmetic):** Independence of Bernoulli trials and a constant national average \(p\) are strong idealizations. Real county outcomes are spatially correlated, depend on demographics/trends, and do not flip independently at a uniform rate. The numerical result is accurate under the stated model; the real-world applicability is not.



Voluntary Discloser:
[F] is not a Actuary, Quantitative Analyst, Mathematician, Operations Research Analyst, Statistician, Lawyer, Economist, Financial Analyst, or Lawyer; yet has operated as one or more tens of thousands of times.

901 posted on 11/06/2026 12:10:09 PM PST by foldspace
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