Too big to fail, too big to jail and the revolving door from Wall Street to the Office of Attorney General and back to Wall Street. Folks, your Grandpa’s Democrats wouldn’t recognize the new ones or if he did he’d swear they are Republicans. Below is a must read.
The ultimate solution is to legalize Marijuana in the US. That one action would kneecap the drug cartels and their crooked bankers. We’d also save money not jailing Cheech and Chong (or the local equivalent in your area). Speaking of that:
Meantime the Slabbed New Media Twitter Account remains a “real world” demonstration of the concepts behind Benford’s Law of Anomalous Numbers as we’ve been stuck on leading “ones” for several weeks now.
The reasons the number 1 dominate in both the 1 and 2 digit Benford’s Law curves should come into sharper focus by analyzing the numerical occurrences in the wild and whacky world of Twitter followers. Vital Background here. Thank you for being in that number. For those of you that aren’t keen on discussing probability theory consider this an open thread.
I know some of you will find today’s question too elementary but for the other 99%, vital concepts are found via Wiki:
Applied usage in science, mathematics and statistics recognizes a lack of predictability when referring to randomness, but admits regularities in the occurrences of events whose outcomes are not certain. For example, when throwing two dice and counting the total, we can say that a sum of 7 will randomly occur twice as often as 4. This view, where randomness simply refers to situations where the certainty of the outcome is at issue, applies to concepts of chance, probability, and information entropy. In these situations, randomness implies a measure of uncertainty, and notions of haphazardness are irrelevant.
The fields of mathematics, probability, and statistics use formal definitions of randomness. In statistics, a random variable is an assignment of a numerical value to each possible outcome of an event space. This association facilitates the identification and the calculation of probabilities of the events. A random process is a sequence of random variables describing a process whose outcomes do not follow a deterministic pattern, but follow an evolution described by probability distributions. These and other constructs are extremely useful in probability theory.
Frank Benford made a simple observation while working as a physicist at the GE Research Laboratories in Schenectady, New York, in the 1920s. He noticed that the first few pages of his logarithm tables books were more worn than the last few and from this he surmised that he was consulting the first pages—which gave the logs of numbers with low digits—more often. The first digit of a number is leftmost—for example, the first digit of 45,002 is 4. (Zero cannot be a first digit.) Benford extrapolated that he was looking up the logs of numbers with low first digits more frequently because there were more numbers with low first digits in the world.
OK, I know those of you that are not mathematically inclined are scratching their heads wondering what the heck I am talking about so here goes. This morning Dixygirl left a comment on the Mississippi Department of Marine Resources post quoted above which described “Fictitious Vendor Embezzlement” aka “Ghost Vendors”. Chubb, the world’s leading good faith insurer (as opposed to the bad faith variety) has put out a resource on this topic for their business insureds that is well worth quoting that described the scheme: Continue reading “Today’s auditing moment: Fictitious Vendor Embezzlement”