WhenExcelFreezesOver

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@EdWhelanEPPC If you think Pratt is anywhere as unpopular as Trump in LA then you are retarded

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@StraightFlorida

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@HotepJesus Based on what?

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@MissInfoShow__ @HardPass4 You can respond with lethal force only if you have a legitimate fear for your (or someone else's) safety

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@BingoBongom6ae @FlopperKev7 @dccommonsense @BrianDBowers @idiotboy1999 Because he doesnt have the jurisdiction?

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@makeapointorgfy @dccommonsense But Pratt didnt finish last

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@DipshitGrimace @dccommonsense @BrianDBowers @idiotboy1999 Plenty of evidence

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@FrankLuntz @ForecasterEnten You dont understand what momentum is and the power it has in politics?

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@BrianDBowers @dccommonsense @idiotboy1999 Dan is asking why nothing has happened yet. It has been under a week. Investigations take time

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@arrowsmith77 @dccommonsense Yeah you caught me

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@rail_breaker31 @dccommonsense Hi Actual Data Scientists, nice to meet you.

https://t.co/FIiAkf0ZGX

[Everette Dobbins @EveretteDo19517]

Who likes math 🤓 This is fun math
The odds of Nithya Raman receiving 40% of the vote yesterday are “LESS LIKELY than picking ONE GRAIN OF SAND on Earth dozens of times in a row.” I believe elections tend to be fair. Someone help me make sense of math that seems impossible…
I ASKED CHATGPT -
“What is the statistical likelihood that 40% of votes from a “new batch” of ballots go to a candidate who received 24% of votes from all other batches that represented 95% of counted electorate. Give me a % odds.”
The Answer (Part 1) -
“Assuming the candidate’s “true” share is 24%, the odds that a random new batch lands at 40% or higher depends on batch size:
50 ballots
0.88%
100 ballots
0.028%
200 ballots
0.00004%
500 ballots
~0.00000000000018%
1,000 ballots
~0.0000000000000000000000000035%”
My follow up -
“Assume 40,000 ballots. Are the odds one in a billion? One in a trillion? Worse? This seems to be happening in Los Angeles Mayor’s race between Mayor Bass, Spencer Pratt and Nithya Raman.”
The Answer (Part 2) -
“If the 40,000-ballot batch were drawn from the same population that produced 24% support in the other 95% of votes, then seeing 40% support in that batch would be far beyond “one in a billion” or “one in a trillion.”
75 standard deviations is in an entirely different universe.
The probability is approximately:
~10⁻¹²²⁰
or about
1 chance in 10¹²²⁰
That’s a number with roughly 1,220 zeros after the 1.
Statistically, if the batch were truly a random sample of the same electorate, the odds are so small that statisticians would effectively treat the event as impossible. The usual conclusion would not be “wow, what a lucky fluctuation,” but rather that the batch is not representative of the earlier ballots—for example, it came from a different geographic area, voting method, demographic group, or subset of voters.
So yes: much worse than one in a billion, much worse than one in a trillion, and vastly smaller than any probability encountered in ordinary statistical analysis.”
My follow up -
“More grains of sand on earth than the likelihood of this?”
The Answer (Part 3) -
“Yes. Much, much more.
Estimated grains of sand on Earth are often put around 10¹⁸ to 10²⁰.
Your odds example was roughly:
1 in 10¹²²⁰
So this is not just “less likely than picking one grain of sand on Earth.”
It’s more like picking the right grain of sand on Earth correctly over and over again dozens of times in a row.”
Sincerely,
Jeremy Padawer
https://t.co/ojIFi3jJOY
@spencerpratt @BoredElonMusk @Hotshot_Movie @415FirePhoto
#losangeles #la #fyp #mayor See less

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@makeapointorgfy @dccommonsense It's not that he would win, but that he would come in 2nd in a primary

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@dccommonsense @BrianDBowers @idiotboy1999 What would you expect to get under a week out from the primary?

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@Raindance_33 @imjeremytho @MatrixMysteries But he got callbacks when he changed his name to Singh

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@coreyhoganyyc This is just an effect of overvalued housing, and just means it's harder for young people to buy homes.
Once the crash comes it'll fall back down. Elbows Up Boomers will cry, but the rest of us will celebrate.

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@JoshKraushaar

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@misterindojin @MatrixMysteries It doesnt work well though as most Indians are not intelligent

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@Raindance_33 @MatrixMysteries How would any of that information be gleaned from a resume?

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@drunknballerina @MatrixMysteries You've never had to work or interact with Indians, have you?

Impossible to hold the opinion that they are smarter on average once you do. Some of them are very good at memorizing (the obsessive Spelling Bee types)