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Friday, March 20, 2009

Hidden Patterns and Statistical Frenzy

I don’t remember how I came across this book — it must’ve been at some used book store several years ago, and I think I read it around 2004. Published in 1992, Predictions by Theodore Modis is what I’d call an intriguing exploration into statistical models about society, and how as a group we follow predictable patterns. While I didn’t understand a lot of the technical talk, I still gleaned enough from it to get me thinking. The reading is sometimes dry — much like this blog post — but Modis makes up for it with content and hopefully bails me out too. There’s something in here to interest everyone, and I’ll offer some of the highlights.

According to Modis and his sources…

Human beings around the world are happiest when they are on the move for an average of about seventy minutes per day. During these seventy minutes of travel time, people like to spend no more and no less than 15 percent of their income on the means of travel. From African Zulus to sophisticated New Yorkers, they are all trying to get as far as possible within the 70 minutes and the 15 percent budget allocation. Affluence and success result in a bigger radius of action. Jets did not shorten travel time, they simply increased the distance traveled.
Industrialization featured mostly muscle-surrogate inventions, but that did not significantly decrease the number of working hours. Allowing eight hours for sleep and a fair amount for personal matters, the time available for work cannot be far from eight to ten hours per day. At the same time, human nature is such that a much shorter work period is poorly tolerated.
Most mammals living free in nature have accumulated about one billion heartbeats on the average when they die. For hundreds of thousands of years, humans had a life expectancy between 25 and 30 years. With the normal rate of 72 heartbeats per minute, they conformed nicely to the one billion invariant. Only during the last few hundred years has human life expectancy significantly surpassed this number, largely due to reduced rates in infant mortality from improved medical care and living conditions. But what also increased at the same time was the availability and acceptability of safe and legal abortions, resulting in a rise of prenatal mortality, thus canceling a fair amount of the life expectancy gains. The end result is that life expectancy at conception is still not much above 40. If there is any truth in this, we are back—or close enough—to the one-billion-heartbeat invariant, but with an important difference. Low infant mortality rates result in the birth of many individuals who may be ill-suited to survive a natural selection process favoring the fittest. At the same time, abortions are blind. They eliminate lives with no respect to their chance of survival. A selection at random is no selection at all, and the overall effect for the species is a degrading one.

Modis uses an S-curve analysis throughout the book with most of his data, showing patterns of early slow growth, then accelerated growth in the middle, followed by slow growth at the end, conforming to a common equation and curve shape. Modis explains the S-curve’s many applications in biology, physics and sociology.

With the S-curve analysis, Modis postulates that based on the number and frequency of the known 45 explorations of the Western Hemisphere following and including Columbus’ voyage (which follow nicely the last three-quarters of an S-curve), there may have been 15 such explorations unaccounted for prior to Columbus, with the first dating back to around 1340.

Modis shows how society made shifts in its energy sources from wood to coal well before running out of wood, and the decline in the use of coal in favor of oil was not driven by scarcity. He predicts that we will stop using oil in favor of some other alternate primary source before we run out of it.

The S-curve pattern is shown to exist with the growth of a bacteria colony, the human birth rate by mother’s age, the demand for plywood, and Ernest Hemingway’s writing career.

Using the S-curve, Modis can back up provocative statements like this:

…better agreement between the curve and the data if eighteen compositions are
assumed to be missing during Mozart’s earliest years. His first recorded
composition was created in 1762, when he was six. However, the curve
extrapolates to reach its nominal beginning of 1 percent of the maximum at about
1756, Mozart’s birth date. Conclusion: Mozart was composing from the moment he
was born, but his first eighteen compositions were never recorded due to the
fact that he could neither write nor speak well enough to dictate them to his
Similarly, for Einstein:
The nominal beginning of the curve points to 1894 when Einstein was 15. This
would mean that he had no impulse to investigate physics when he was a child.
According to the curve, this impulse started when he was a teenager. Still, he
produced no publications until the age of 21, probably because nobody would take
the thoughts of a mediocre teenage student seriously, let alone publish them.

It’s fun to extrapolate and attempt to fill in the gaps of what we don’t know. I like to think of life as a bunch of clues waiting to be uncovered. There’s so much we don’t know, but I’m of the opinion that a great deal is at our fingertips and can be revealed if we look in the right ways.

Modis then goes into an analysis of regular societal fluctuating periods of about 50-60 years ever since about 1800 (when data became more readily available). In these periods, various trends go through an upward and downward curve before returning to the same point, over the same period of time, and many occur independently of one another, existing in their own phases. He talks about energy consumption, innovations and life expectancy, among other things. Modis shows the periods where major modes of transportation reached the midpoints of their paths, each separated by 55-56 years: canals from 1836 to 1891, railways from 1891 to 1946, roads from 1946 projected to 2002 (?), followed by airways, which should then be replaced by some other means (Modis predicts the Maglev train) at its midpoint around 2058.

The author also says:

A period of 56 years is close to the length of time an individual actively influences the environment.
The smallest integral year time unit that allows accurate prediction of eclipses at the same place is a total of 56 years. the 56-year period concerns not only eclipses and the alignment of the earth, moon and sun on a straight line. Any configuration of these three bodies will be repeated identically every 56 years.
There are 56 holes, the so-called Aubrey holes, equally spaced in a circle around Stonehenge. By using the Aubrey holes to count the years, the Stonehenge priests could have kept accurate track of the moon, and so have predicted danger periods for the most spectacular eclipses of the moon and the sun.
Humans spend the first 28 years of their lives acquiring or “charging,” first an affective, then a physical, then an intellectual, and finally a spiritual capability, each building successively on a seven-year spiral. The second 28 years see the human in a state of “tension” as parent, contributor to society, thinker. The final 28 years the person becomes “discharged” affectively and spiritually, reaching the full age of three times 28.
The period 1996 to 2024 should be a period of growth leading to prosperity not unlike what happened between 1940 and 1968.

I’m not taking all of these hypotheses necessarily at face value, but it’s still interesting to look at a lot of this phenomena from another perspective and note the patterns. I like books like this. If you know of any others you can recommend, tell me about them. This one can be bought used on Amazon for about $5.00: Predictions, by Theodore Modis.

Do you ever wonder what kind of patterns you might be following? Would it cause you to alter them if you were aware of it? I think it possibly would. After all, it becomes rather difficult to throw out all subjectivity when making judgments while being aware of such things. It's a little hard to pretend to not know what you do.

It would be fascinating to me to have access to statistical information about my life and those around me, and see patterns about how we all behave and think. Then would could more easily accentuate the positive and eliminate the negative.

I’d like to know how many times in my life I’ve said words like exquisite, scintillating, juxtaposed, lackadaisical, gumption and hackneyed. And then compare it to the general public. I’d like to know what the ten most frequent meals I’ve eaten are, and the quantities of each. I’d like to know how many people I’ve known on a first-name basis in my life. I’d like to track exactly how much sleep I’ve gotten each night, and see what the patterns are there. I’d like to know how many words I’ve typed. I’d like to see how centered I’ve kept cars I’ve driven in their lanes, what my average speed has been with relation to the speed limit (probably 4-5 mph over on highway, and 2-3 mph over in city — your mileage may vary). I wonder how many sunflower seeds I’ve eaten. Possibly over a million. By age 14. I wonder how many ants I’ve stepped on, both intentionally and unintentionally. I wonder how many times I was called out in baseball/softball when I was really safe. I wonder what my least accurate memories are. I wonder how many things I’ve learned from various people throughout my life. That last one never ceases to amaze me. You think you’ve got a lot of it down, but you just keep on learning more and more, when you least expect it. Life is a neverending tapestry of discovery.

If my whole life had been tracked by Twitter, I could know how many times I’ve said each word. It would also be interesting to see how my language patterns changed with age. We can estimate a lot of these things. Maybe Charlie from the TV show NUMB3RS could narrow it down pretty good.

I just think it would be so mind-boggling to have a book of your life to peruse through. I hope somebody's working on that.

Then it would also be fun to quantify things that aren’t normally quantifiable, like emotions. Maybe that’s a little over our heads right now. As humans, we can barely handle the information that we do have. It’ll be a while before we’re ready for radically new types of data.

Anyway, thanks to Theodore for giving us another little peek into some of these things that make you pause and go hmmm…

1 comment:

Doug and Laura said...

This article was very interesting. I have never heard of his work before. It does make sense. I would be interested in some statistics about babies, i.e. their crying, pooping, stuff like that. I guess that is the mode I am in right now.

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