The odds, it’s something each of us faces daily. What are the odds that:
- You’ll arrive safely home after a long day at work?
- Not spill coffee on your nice, new shirt?
- Get Covid-19 (or is is 21 now?) from making eye contact with an “asymptomatic carrier” across the restaurant?
We get so used to beating the odds (the chance of getting in a car accident is 1 in 289, but you don’t get into a car accident every 289 trips) that we mostly just forget about these things. Unless of course you’re into gambling, then odds are very important.
Speaking of odds, did you know that the Nevada state gaming commission, has taken over a portion of election integrity? You know that saying, “The house always wins?” Kinda funny, considering what’s going on. Makes one wonder: who’s the house?
Of course, the odds in an election shouldn’t be decided by “the house.” It should be decided by the people. That’s the whole point of this experiment called America- the people get to decide. Yet, there’s all this evidence seems to indicate otherwise.
Just the simple fact that we are told, “Sit down and shut up” or “That’s not for you to know,” is a pretty big indicator. That Secretaries of State gathered nationwide to prevent question asking, is another red flag. Smacks of the whole, ‘Rules for thee are not for me,’ thing that pioneers fled, hundreds of years ago.
America is supposed to be all about equality, but not the kinds of “equality” we see in our elections. What we are seeing is, unfortunately, not that whole antiquated notion of one person = one vote. No, the kind of equality we see in the 2020 General Election is where great swaths of people, millions in fact, had exactly the same opinion.
Example #1) At 10:48 pm 11/03/2020 in Nevada 1,039,324 votes had been counted and the Trump to Biden ratio was 95/100. Despite the fact roughly 1,312,469 votes were counted over the next few days the ratio of Trump to Biden votes NEVER varied, not once. That’s some amazing “equality,” the kind where everyone has the exact same thoughts.
Of course, technically speaking, that’s equity, not equality. There’s a big difference (in case you didn’t know). Equality means everyone starts out as equal as possible, given that we are all human and no two of us are 100% identical. Success or failure however, is up to the individual. Equity on the other hand, means everyone ends as equal as possible. Even if everyone is failing, in equity, that’s “great.”
Example #2) Minnesotans are also, apparently, very like minded people.
As a natural phenomenon, that’s some pretty amazing stuff right there. (Yes, it’s a lot of numbers, the point is that the ones in the red circle are all the same and they shouldn’t be.) To roughly quote Professional Engineer, Draza Smith, ‘What is the probability of having the same value reported for 57 data sets in a row?’
Also, don’t pay any attention to the multiple instances of a single vote being counted as 45.35% for Trump and 52.55% for Biden. Nothing to see here. According to some, Edison Research, this is just a prediction… that is at the very least, collected from the Secretaries of State, used by the media to inform the nation of the election results, and the guideline for determining the winner.
The Secretary of State’s office in North Dakota has been reported to have confirmed that these are not in fact “just mathematical projections” but real time data that is regularly reported from their office, to Edison Research, who then transmits the data to the media.
Regardless of which is true, both agree that the end the results are verified to make sure they match the Secretary of State and if they don’t, well… no biggie. Just a little subtraction, from both candidates, at the exact same ratio of the “prediction.” (Well, not always. Sometimes, things just had to be fudged.) I’m certain, that there’s nothing funny going on…
Example #3) Okay, but that’s just one race. (Ahem… that’s two thus far, but I see your point…) What will we see if we look at more than one race?
The correlation coefficient, or R value, is a mathy way to verify how similar two things are, aka a “statistical measure of the strength of the relationship between the relative movements of two variables.” The values range between -1.0 and 1.0. A correlation of -1.0 shows a perfect negative correlation, while a correlation of 1.0 shows a perfect positive correlation. A high R (above 0.81), tells us that the things we are comparing are so closely connected that with one value, you can simply create the other value with math. For example, if you know the votes for a candidate in Sacramento (next graph, District 7), then you can calculate the votes for the candidate in Oakland (District 12). You don’t need ballots, or people. In fact, one independent election analyst has said that if you asked humans to intentionally create this scenario without a computer, they couldn’t do it.
Okay but those are all in one area, or one state. Of course, there are “similarities”. Right? I mean do the people of Santa Clara, population 132, 925, average income $115,000 really vary that much from District 43 in LA, population 748,092, average income $38,671? Surely, there’s not that much variation in the people of Utah or North Dakota. I bet oil patch workers have the same values as farmers who have the same values as those Microsoft employees and world-traveling surgeons in Fargo. Come on… it’s fly over country, cookie cutter people, for certain. Pfft… It’s not odd at all that there was no variation in the last 31% of votes “counted” in North Dakota, nor the last 42% of Nevada. No one will notice, I’m sure. Moms are supposed to have Easy Bake Ovens for stomachs and diapers for brains. By the way, it doesn’t matter now. The election is over, sooo over. Anyway, so what… states that match. Bet that doesn’t happen much…
We can just file this last one under the heading “The Dakotas.” They should like totally be one state anyway. It’s no big deal that they were all matchy-matchy. Of course North Dakota, chose a software developer, specializing in fake crying in TV, whose website instructs you to schedule “an appearance,” for governor, while South Dakota chose a bona fide cowgirl, whose website is pretty much her photo and her phone number, and who has enough cohones for both states. But sure, we’ll pretend they are the same…
Well, here we are. Congrats. Now that you’ve read all of this (and my super snarky commentary), is your mind boggled? Mine is. What next?
One last question:
What are the odds of these “matches?” If you look up “odds of finding a match” on the internet, you’ll find yourself swamped with match-making advertisements for days. I don’t recommend it. Probability statistics is a better search term. Here’s where we get back to the odds and the house.
What are the odds that you will have two cards that match (a pair), when dealt a hand in poker? 1 in 16 or 5.88%. If we apply the same concept to elections, well there really shouldn’t be any pairs. However, we can look at how many possible outcomes there are. To do that we need to understand the variables:
- States – 50 (plus the District of Columbia)
- Counties – 3,142
- Election Equipment Manufacturers – 9
- EAC Certified Systems – 71
- Candidates – 9,671
- Time zones – 4
Altogether, that’s 3,961,034,176,392 possible outcomes. If you have one set of election results in hand, the odds of finding a second that matches it should be astronomically high because, well there really shouldn’t be matches. But assuming you could find one, the odds would be about 1 in 3,961,034,176,392 chance of finding a match. Which, I guess, qualifies as astronomically high.
If we are only comparing the presidential race, then that reduces the odds to 1 in 1,024,083,177 (when including five candidates, it’s 1 in 409,633,271 when only including two candidates). A significant improvement on the impossible. Yet, those graphs above, still shouldn’t be happening. If a 1 in 289 chance of getting into a car accident does not result in a car accident every 289 times driving, then a 1 in 1,024,083,177 chance of finding a match ought to be near impossible. In just the state of California, there were 308 candidates, 58 counties, (1,000 polling locations) and 8 election equipment manufacturers, 30 election equipment systems or 4,287,360 possible outcomes. Again, the likelihood of finding a match, well it’s not supposed to be very good.
Finally, one might argue, that when a group of individuals in one area is forced to choose between just a few candidates for one elected position, this is just what happens. To that, let me present:
Thus, if you knew what the votes for Mfume (the winner in that race) in Maryland’s 7th District were, you could calculate how many votes Trump would receive in the state of California, without using ballots. Makes complete sense right?
So… what are the odds? Do you think that these are natural occurrences?
The comparison between Alaska and Delaware was not as well matched as initially thought. There was a error in the spreadsheet that is very likely, entirely my fault. The information has been removed and I sincerely apologize.