Lord Monckton’s Mathematical Folly (Or, Odds Botchkins!!!)
Well, math is certainly not my strong suit so I am probably going to regret this one, but nobody has tackled Lord Monckton of Brenchley’s Eligibility Odds analysis yet. Except that I found after doing this Internet Article, that Dr. Conspiracy had just finished one, too. So here is the link to his, too:
http://www.obamaconspiracy.org/2012/09/miscalculating-the-odds/
Anyway, here is the relevant excerpt from the World Net Daily Internet Article, and the link to the whole article follows the excerpt:
OBAMA ELIGIBILITY ODDS: 1 IN 62.5 QUINTILLION
Lord Monckton crunches the numbers
He cites:
1. The fact that the registrar’s signature-stamp on the electronic form can be moved about: 100:1 against.
2. Registrar’s date-stamp ditto: 100:1 against.
3. Multiple 1-bit monochrome layers and one 8-bit color layer: 60:1. (Experts twice found no such pattern in 600 file-optimization programs: I allow for 10 anomalous programs to exist.)
4. “Lavishly funded bureaucracy uses wonky typewriter:” 10:1
5. Human error: Certificate number out of sequence: 25:1
6. Incorrect birth date of father: 40:1
7. Use of “African” contrary to written form-filling rules and 20 years before the term came into common use: 25:1
8. Miscoded statistical data: 25:1 (official government estimate).
9. White halo around letters: 10:1
10. Chromatic aberration absent: 100:1
11. Other identity documents: Anomalously worded abstract on short-form birth certificate: 100:1
12. Two-digit year on selective service stamp against DoD written rules: 100:1 (actually impossible: no two-digit example other than that of Kenya’s “son of the soil” is known)
13. Non-citizen of Connecticut holds Connecticut social security number: 100:1.“There are many other errors, but these suffice. Defenders of Mr. Community Organizer say each error could have just happened by accident. I mean, it’s government form-filling, right?,” he wrote. “But here’s where the math comes in. If each error is a genuine accident, the errors are independent events, so the probabilities of each error are multiplied together to determine the probability that all occurred in one document.
“Thus the odds against all of these errors occurring in a single document except by design are 1 in 100 x 100 x 10 x 10 x 25 x 40 x 25 x 25 x 10 x 100 x 100 x 100 x 100. Accordingly, the probability that Mr. Obama’s birth narrative is in substance true is no better than 1 in 62,500,000,000,000,000,000, or 0.0000000000000000000016.”
He wrote, “Don’t be misled by the simplicity of the method. It’s simple but sound.”
http://www.wnd.com/2012/09/obama-eligibility-odds-1-in-62-5-quintillion/
First, let’s look at the method of determining the odds, from this website:
http://mathcentral.uregina.ca/beyond/articles/gambling/odds.html
Independent vs Dependent Events
People often misunderstand the notion of independent events. This is a probability term meaning that past events have no influence on future outcomes. For example, when flipping a coin four consecutive times, the probability of getting four heads is:
This is because the probability of flipping a head if you flip a coin once is ½. Flipping a coin is an example of an independent event. When flipping a coin, the probability of getting a head does not change no matter how many times you flip the coin. When the coin is flipped and the first three flips are heads, the fourth flip still has the probability of ½ However, many people misunderstand that the first three flips somehow influence the fourth flip, but they do not. The probability is still the same, as if the first three flips had never occurred.
This is simple so far. You put the chance of something happening in the form of a fraction for each event, and then multiply the numerators and denominators. So let’s try it! Pull out 5 cards. Make 3 of them face cards. Turn them over, and pick one. What are the odds it will be a face card? 3 chances in 5. Pick out a second set of 5 cards with 3 of them being face cards. Now turn each set over and pick one card from each set. What is the chance both of them will be face cards??? 3/5 x 3/5 = 9/25.
Now we have the basic math down. Plus we learn something interesting. The more events you have with a fraction less than 1, the more the odds go up. With one set of 5 cards you had a 60% (3/5) chance of drawing a face card. With 2 sets you have a 36% (9/25) chance of drawing 2 face cards. Monckton has a 13 series of events above, so his game is rigged from the outset to result in lower odds.
Let’s move on to some more concepts. Take the 5 card set and a penny. The cards have a 3/5 chance of a being a face card, and the penny has a 1/2 chance of being flipped ”heads.” Multiply those fractions and you get 3/5 x 1/2 = 3/10. But what does the 3/10 represent??? It can’t stand on its own as just a number without describing in more detail what it represents. Which in this example is the chance of drawing a face card AND getting “heads” on the flip.
Now, let me add a third item to these two, with some dice. What are the odds of me rolling box cars, or double sixes??? Those odds are 1 in 36, or 1/36. What are the odds of drawing a face card from the five card set, flipping “heads” on the penny, and rolling a double six??? Here’s the math: 3/5 x 1/2 x 1/36 or 3/360 or 1/120. But the question arises, “What am I really measuring???”
Let’s make it more interesting still. What are the odds that I will break a nail while picking a card, flipping a coin, and rolling the dice??? I put those odds at 1 in 100,000. Now what am I up to in the odds? Here’s the math: 1/120 x 1/100,000 = 1/12,000,000 or 1 in 12 million. But the question arises once more, “What am I really measuring???” These are unconnected things. I am picking the card, flipping the coin, rolling the dice, and breaking a nail all on the same desk top. What are the odds of that happening on the same desk top??? The answer is 1 in 12 million, but as you can see this is a basically meaningless number.
But I am still NOT happy with this number. I want it to be higher. Sooo, I am going to find a non-event, assign odds to it, and put it into the math mix. What I need for my non-event is something that either doesn’t happen at all, or if it does happen, it is not really what we normally think of as a measurable event, such as flipping a coin. How about how many times does McDonalds fail to give me ketchup with my drive thru order. That’s about 1 time in 4, or 1/4. That makes the odds for everything (pick face card, flip “heads”, roll box cars, break a nail, and fail to receive ketchup) about 1 in 48 million. See how easy it is to work your way up?
But, the McDonalds non-event needs more explanation. Simply not getting ketchup may not be an event at all because it is possible that I only ordered coffee at the window, and that typically does not require ketchup. Or, it could be that I ordered a dinner meal and no fries. Or, I just wasn’t feeling like ketchup on that trip, and so did not request any. Or, that I had some extra ketchup in the car. Trying to pin a set of odds on a situation like that is very problematic. It is possible it wasn’t a failure at all.
Monckton slyly engages in this same practice. He mixes facts and conjectures about an electronic image and tries to make the nexus the fact that they all occur about the same document. He goes further, because he also picks some events which are not agreed to constitute events by the non-Birther side. This is like saying “heads” were flipped, when one party to the action does not believe the coin was flipped at all. But Monckton makes the leap, and then assigns those contested facts odds as if they were not contested. This is great if you trying to run the number up, but pretty much meaningless for any other purpose. It will take a while, but let’s examine Monckton’s 13 so-called independent events in more detail.
1. The fact that the registrar’s signature-stamp on the electronic form can be moved about: 100:1 against.
I am going to call this one a non-event. This is more like saying the coin exists, but it has not been flipped. The signature stamp on the paper document can not be moved about. If it can on the electronic image, it is not necessarily indicative of anything wrong.
2. Registrar’s date-stamp ditto: 100:1 against.
I am going to call this one a non-event, also. The date stamp on the paper document can not be moved about. If it can on the electronic image, it is not necessarily indicative of anything wrong.
3. Multiple 1-bit monochrome layers and one 8-bit color layer: 60:1. (Experts twice found no such pattern in 600 file-optimization programs: I allow for 10 anomalous programs to exist.)
Three time’s the charm, I guess. I am going to call this one a non-event, too. There are no layers on the paper document. If there are on the electronic image, it is not necessarily indicative of anything wrong.
4. “Lavishly funded bureaucracy uses wonky typewriter:” 10:1
I’m sorry. Has the Hawaii DOH been shown to have been lavishly funded in 1961? Did I miss that? And what is a “wonky” typewriter as compared to a non-wonky one? If we are going to go all mathy on this, can we at least get some discrete measurable independent events???
5. Human error: Certificate number out of sequence: 25:1
I am beginning to see a pattern here. Monckton is choosing things which are NOT events at all. There is NO proof that the certificate number is out of sequence. In fact, Alvin Onaka. Ph.D, Hawaii State Registrar has thrice verified the number as correct.
6. Incorrect birth date of father: 40:1
This is not a measurable event to which you can assign odds. No one knows what caused it. Was it a typo, or did somebody lie, or did somebody just mess up by accident???
7. Use of “African” contrary to written form-filling rules and 20 years before the term came into common use: 25:1
Again, a non-event. This isn’t contrary to anything. The Cold Case Posse used the wrong coding book. I am becoming disappointed in Lord Monckton. We are halfway through this stuff, and there has not been one single discrete measurable independent event.
8. Miscoded statistical data: 25:1 (official government estimate).
What miscoded statistical data??? The penciled in “9″ is the correct number. Zullo and Corsi were using the wrong coding manual.
9. White halo around letters: 10:1
Are we back to non-events again??? This is on the electronic image. There are no white halos on the paper document.
10. Chromatic aberration absent: 100:1
Damn non-event again.
11. Other identity documents: Anomalously worded abstract on short-form birth certificate: 100:1
Nope, he’s gone to a different document to multiply against the long form birth certificate. This is just for the purpose of making the number larger, like me adding broken fingernails to the discrete measurable events.
12. Two-digit year on selective service stamp against DoD written rules: 100:1 (actually impossible: no two-digit example other than that of Kenya’s “son of the soil” is known)
Nope, again. Different document. Same reasoning as 11 above. Plus, there is no evidence that the stamp wasn’t broken. How many 1981 documents from that post office have been analyzed???
13. Non-citizen of Connecticut holds Connecticut social security number: 100:1.
This one might be a keeper, although it doesn’t relate to the birth certificate. There probably is a way to measure how often the SSA assigned group numbers to non-residents of the state. But that doesn’t prove anything was wrong. It could have been a typo.
Now I am kind of irritated here. I went and studied up on some math, and practiced multiplying fractions and Lord Monckton didn’t have but one marginally measurable event out of 13 alleged independent events. Everything else was an alleged incongruity of some sort, but mostly on the electronic pdf image. In other words, because Corsi and the Cold case Posse couldn’t figure out how the paper document was scanned and uploaded, they came up with a bunch of ALLEGED errors, which His Majesty, or whatever you call him, tried to shoehorn into a phony probability analysis.
What is the chance that was an accident on Monckton’s part??? Let’s see, if we assume there is a 1 in 2 chance it was an honest boo-boo on his part, and we have 13 boo-boos, then 1/2 to the 13th power equals 1/8192 or 1 chance in 8,192 that it was an honest mistake.
For shame Lord Monckton of Brenchley!!!
Squeeky Fromm
Girl Reporter
Note 1. The Image. This is from the 1931 film, Dr. Jekyll and Mister Hyde.
Note 2. Links. Here is the previous article about Lord Monckton:
Note 3. Odds Botchkins. This is a word play on the epithet, Odd Bodkins:
Odd’s bodkins is a mild profane oath, which literally means ‘God’s dear body!’ It’s now archaic, but was used as an exclamation like God damn! or a host of others.
The usual form of the second word is bodikin, which is a diminutive of body (the diminutive suffix -kin is found in such other words as lambkin). The expression occurs in Shakespeare (Hamlet: “Odds bodikins, man,” with a variant reading from the Quarto of “bodkin”), Fielding, and Smollet, among others. Expressions like this were very common in the sixteenth and seventeenth centuries; some other examples are ‘sblood (God’s blood), ‘snails (God’s nails), zounds (God’s wounds), and gadzooks (God’s hooks).
The word is unrelated to bodkin ’a small dagger or pointed instrument’, which itself occurs in Hamlet, in the “to be or not to be” speech (“He himself might his quietus make with a bare bodkin”). This word dates back to the fourteenth century, and is of uncertain origin.
Botch means to mess something up.
Blowing Smoke means bragging or boasting. (Blowing smoke is similar to “hot air;” it has little substance, and dissipates rapidly.)
2012-09-27 20:18:20
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