A New Explanation For the Plight of Winter Babies

The initial comments at slashdots focuses on the accuracy of the data and soon shifted to speculation of the causes. In his book Outliers: The Story of Success, Malcom Gladwell writes about the birth month of players in the Ontario Junior Hockey League. More players were born in January than in any other month. Why? Read Chapter 1 of the book.

Want to know the answer now?

The explanation for this is quite simple. It has nothing to do with astrology, nor is there anything magical about the first three months of the year. It's simply that in Canada the eligibility cutoff for age-class hockey is January i. A boy who turns ten on January 2, then, could be playing alongside someone who doesn't turn ten until the end of the year—and at that age, in preadolescence, a twelve­-month gap in age represents an enormous difference in
physical maturity.

This being Canada, the most hockey-crazed country on earth, coaches start to select players for the traveling "rep" squad—the all-star teams—at the age of nine or ten, and of course they are more likely to view as talented the bigger and more coordinated players, who have had
the benefit of critical extra months of maturity.

And what happens when a player gets chosen for a rep squad? He gets better coaching, and his teammates are better, and he plays fifty or seventy-five games a season instead of twenty games a season like those left behind in the "house" league, and he practices twice as much as, or even three times more than, he would have otherwise. In the beginning, his advantage isn't so much
that he is inherently better but only that he is a little older. But by the age of thirteen or fourteen, with the benefit of better coaching and all that extra practice under his belt,
he really is better, so he's the one more likely to make it to the Major Junior A league, and from there into the big leagues.""

The cause, suggested by the original researcher can be found here.

Computer Program Self-Discovers Laws of Physics

While I have not given sufficient thinking on the implication of "The Petabyte Age" to have proper comment, I want to point out my underlying stance for scientific theory.

Science focuses on repeatable observable events. We throw a stone up, it falls back down. Do it again, it falls again. So, we try to *understand* a collection of similar events (throwing the stone up, forward etc) by proposing a theory. The utility of the theory is that we can use the theory to *predict* similar events.

As we progress, and hence have accumulated more observations, we want to develop more powerful theory which can predict more types of events. When one theory can also *explain* (i.e. predicts events) other events covered by other theory, we choose the more powerful theory.

At the same time, as the accuracy of observation increases, the demand on the theory also increases. The theory needs to predict to the same or higher accuracy of the observations.

An example is the relationship between Newtonian mechanics and Einstein's relativity. At human speed, Newton's laws of motion is perfectly fine in predicting the velocity of objects. As the speed approaches that of light, we need relativity to predict the velocity. However, at the same time, Relativity also produces the same prediction of velocity at human speed albeit the mathematics is more involved.

I also noted two interesting points on this process.
1. Terms are coined to represent very specific ideas used in the theory. For instance, momentum is defined as the mass times velocity. Such concepts are useful shorthand which can reduce the complexity of the theory.
2. Inevitably, mathematical models are used. Mathematics are tools developed entirely based on logic. In its purest form, mathematics are not independent of evidence or observation. Mathematics are pure conceptual construct - an art. Scientists find the logical deducing power of mathematical model useful to express complex observations. Almost all major advances of physical science is pre-dated by the development of a powerful mathematical tool. Most physical theories are now expressed in mathematical form.

The combination of (1) and (2) above makes learning science a highly demanding task. There are lots of terms to learn. These are concept shorthand and conventions. In order to be able to understand the theory, we must have working knowledge of all the terms used. As many physical theories are expressed in mathematical form, we must also have working knowledge of the system of mathematics which is used by the theory.

With these observations, I am not sure computer-based generation of theory would be useful for our understanding of the physical realm we live in.

Whatever happened, don't give up.

Random Acts of Kindness

Does Random Acts of Kindness still exist?

Think before you post

Online Sexual Exploitation