What Science is ... and isn't

What Science is .. and isn't.
(C) 2007 -- all rights to revise reserved.

If an armadillo is killed crossing the road near Dallas, Texas, how is the price of yams affected in Namibia? Silly question? Mayhap not. It would certainly be a good starting point for a thriller novel. What has that to do with Science, though?

Life is filled with uncertainties. Events occur on the other side of the world that affect people who may never have heard of the people or places involved. Man has always been fearful of uncertainty, and has devised many ways of dealing with his fears.

From earliest times, magic and consultation with spirits was considered the only way to foretell what was going to happen in the future. Superstitions arose regarding almost every aspect of life. B.F. Skinner brought the concept of superstition into the modern realm with animal experiments, and helped his students visualize what occurs in the making of a superstition. He did not admit to cognitive thinking, so he couched his explanation in behavioral terms. Essentially, according to Skinner, superstitious behavior results when random activity is positively rewarded.

To many people, there is no distinction made between superstition and religion. It is easy to see why; the religious beliefs of many people are indeed founded in the reinforcement of superstitious behavior. Unfortunately, the same can be said of the scientific beliefs of many people as well.

I have to say that I went through high school and obtained a bachelor's degree in education, with a major and minor in physical and biological science education, without having been exposed to the philosophy of science. Certainly I had been well drilled in the "scientific method", but a number of the things taught were erroneous, and others misleading. The major error involved the concept of "proof" in science.

As noted in the beginning of this post, life is filled with uncertainties, and the purpose of science is to reduce those uncertainties and improve the quality of our decision-making. It was not until I took a post-graduate course in educational statistics that I was finally clued in to what science can and cannot do (Thank you, Dr. Isidore Newman!). The dirty little secret is that science cannot provide proof of what is true; it can only provide proof of what is false.

Think of it this way. I reach into a bag of hundreds of marbles, a bag into which I cannot see, and withdraw a marble. I do this 100 times. Each time, I withdraw a white marble. Have I proven that the bag holds only white marbles? No, because on the 101st try, I just might come up with a red or black or green marble. Can I expect that on the 101st try I will grab a white marble? Yes, because my experience provides a probability of 100 out of 101 tries that the marble will be white. It does not guarantee, however, that the 101st marble will be white, and does not prove that the bag contains only white marbles.

Experimentation and experience (largely the same thing, with differences in the degree of controls) provide us with probabilities that something will or will not happen. For this reason, it is critical to understand that the correct use of the scientific method is not to test a hypothesis, but to test a null hypothesis. We can be certain of what we have observed, and develop a prediction of what will happen in the future, based on what we have experienced in the past. I can say of the marble bag, that the probability of drawing a white marble is 100%, based on my experience, but I CANNOT say that the bag holds only white marbles, until I have completely emptied it, in which case I need not make any predictions about future drawings. I have proof when there is no longer any reason to predict because I have exhausted all possibilities; I have removed all uncertainty.

In order to make sense of the world around us, we develop theories about how things work. The theory may be based on superstition, and most likely is. As a result of having created a theory, we then form a hypothesis to indicate what we expect the results of an action will be.

Suppose I generate a theory that states that all bags containing marbles contain only white marbles. I have based this theory on the fact that I have reached into a marble bag 100 times, and 100 times I have pulled out a white marble. Have I proven that marble bags contain only white marbles? My experiments have 100% results. If someone asks me to gamble all of my possessions now and in the future on whether or not the 101st marble will be white, am I willing to trust the 100% results of the past?

If, however, I generate the theory that all bags containing marbles contain only white marbles, and that I will NOT withdraw anything but a white marble, then I can test that null hypothesis by experimentation. I can accept the null hypothesis with a percentage of certainty. If, however, I ever come up with anything other than a white marble, I must reject my null hypothesis, and at that point may have to admit that I have DIS-proven my theory. Or, as more commonly happens, I would modify my theory to state that in most cases, the marbles in a bag will be white, or that the majority of the marbles in a bag of marbles will be white.

While this may seem to be an exercise in semantics, it is critical to real-life operations. It is an observable part of human nature that the normal reaction to a situation that has gone wrong is to find someone or something to blame for the failure. Thus it was that some 40 or 50 years ago (my, how time flies!) the meteorologists switched from saying that today's weather would be rainy to saying there was a 70% chance of rain. It caused some consternation, and there are still some folks who are very unhappy about that kind of forecast, but it took the blame away from the weatherman. If he said there was a 70% chance of rain, and you gambled on the 30% chance of dry and got wet, it was your own decision, not his. Enough for now, but we will have to look next at the pseudo-science of legal proof, which has totally corrupted the American system of justice, and is widely used by dishonest politicians (most of whom are lawyers!).