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"theory" And The Scientific Method

Guest Davka

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The-o-ry (noun)


1. a coherent group of general propositions used as principles of explanation for a class of phenomena: Einstein's theory of relativity.

2. a proposed explanation whose status is still conjectural, in contrast to well-established propositions that are regarded as reporting matters of actual fact.

3. Mathematics. a body of principles, theorems, or the like, belonging to one subject: number theory.

4. the branch of a science or art that deals with its principles or methods, as distinguished from its practice: music theory.

5. a particular conception or view of something to be done or of the method of doing it; a system of rules or principles.

6. contemplation or speculation.

7. guess or conjecture.


The word "theory" has a very different meaning in science than it does in common useage. Outside of science, "theory" can be used as a synonym for "idea" or even "educated guess" (meanings 2, 6, and 7 above). But in science, that's not a theory, it's only a hypothesis. Scientific theory deals only with the first definition, "a coherent group of general propositions used as principles of explanation for a class of phenomena."


Following is a brief explanation of the Scientific Method, and the use of the word "theory" in science.


When creating a scientific theory, step one is to observe. Look around, see what's going on, take some notes.


Step two is to come up with a possible explanation of why things are happening the way they are. This is called a hypothesis. Lots of people mistake a hypothesis for a theory, but they are not the same. In order for your hypothesis to become a theory, it has to pass some tests.


The way to test a hypothesis is this: you come up with a prediction based on your hypothesis. I might hypothesize, for example, that there are so many SUVs in the South because there are more fat people in the South. I would then predict that, on average, fat people in the South drive SUVs more than they drive sedans. Now I have a testable hypothesis - and this is important, because if it's not testable, it's not science.


You must be able to create a predictive model in order to test a hypothesis.


So let's say I set up an experiment to test my SUV hypothesis. I'm going to hang out in a parking lot all day and count the people going in and out, taking notes on whether they are fat and what kind of car they drive. And - ta-da! I discover that yes, fat people are statistically more likely to drive SUVs into my parking lot than other cars. I have the foundations for a new predictive model of Fat SUV drivers. And, like a good scientist, I publish my results in the Journal of Scientific Fatness and SUVs.


But this is where tragedy strikes. Why? Because other scientists read my report, and they decide to set up their own experiments, to test my theory. One of them goes to a different parking lot, and gets conflicting results. Another polls people who are shopping for cars, asking what factors influence their decisions. And both of these scientists publish their results, which disprove my original hypothesis. It is not accepted by the scientific community as a valid theory. My life is over.


My model was predictive, but the predictions it made were wrong. It never progressed from hypothesis to theory.


This is the way to get from observation to theory:


1) Observe


2) Hypothesize.


3) Predict.


4) Test your hypothesis.


5) If it accurately predicts, you have a predictive model. Publish for peer review.


6) Get other people to repeat your experiment. if it passes, then


7) Come up with more, different predictions based on your hypothesis, and test it some more.


A hypothesis becomes a theory only after it has been established to have reliable, repeatable predictive power. When many different people have devised many different ways to test the hypothesis and it proves to be an accurate predictor of outcomes, then and only then is it accepted as a theory.


But it doesn't end there.


Theories are continually undergoing more and more tests as we learn more. Sometimes theories are revised, or scrapped altogether when new information is discovered. This is what a scientific theory really is: a predictive model that has proven accurate to a large group of people over a long period of time.


Evolutionary theory has done this. It has also been revised as new information comes in. Darwin's original theory has not held up in all areas, because science has made new discoveries about the way the mechanism works. These new revisions have fine-tuned the predictive model.


Evolution says "if this theory is true, then we should find X type of fossils." And we do. It says "if this theory is true, then amino acids should behave in a particular fashion under certain conditions." And they do. The predictions based on evolutionary theory can be tested. They are tested. So far, the theory has held up very well under the pat 150 years of repeatable experiments.


So-called "creation science," on the other hand, has no predictive model at all. I cannot think of a single prediction made and tested by a Creationist. I've never heard of such a thing. That's because it's not even a theory, it's just an opinion. Not only can it not be "proven beyond a shadow of a doubt," it can't be proven at all.


This, in a nutshell, is the real difference between what science calls a "theory" and what non-scientists call a "theory." Creationism has no testable hypothesis, it is simply an idea. It has no more or less weight than any other untested and untestable idea. Creationism truly is "only a theory" in the sense of being someone's wild hair idea.


But the Theory of Evolution is based on numerous testable hypotheses which have undergone 150 years of peer review. It is a Theory in the scientific sense of the word, not the common sense.

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Guest marabod

This would be not a universal form of scientific approach, but only the methodology, used in non-precise, in Observational sciences like Biology, Sociology, Psychology, Economics etc. These sciences are observing the facts, creating their statistical picture, explaining the known facts with hypotheses and theories and at their highest point they use the theories to predict the facts. The only area of Mathematics, applicable to these sciences is Statistics, and their most practical output is either a Theory which explains the facts and predicts new facts, or a Method (how to practically achieve something on the basis of some Theory).


This approach does not work with precise sciences, either Applied or Theoretical. Theory in them is not an explanation of facts, but a Mathematical model, connecting these facts together. This model is always established not on the statistical basis of observations, but on the basis of Formal Logic, and does not use Statistics at all. When a hypothasis, Working hypothesis or a Theory provide the "verbal explanations" they are only valid if they are based on the Mathematical Model - this is the core difference between a Physical or Chemical Theory from such thing as Theory of Evolution, which is observant and statistical by its nature. It is enough to compare it with Special Relativity theory to understand the difference.


Also, a Theory for such sciences as Physics and Chemistry is not the top possible output at all, as they target to establish the Laws of Nature, which are then used as a base for new technologies and products. Theories with no practical application are not treasured in these sciences - classical example is that Einstein was never anyhow awarded for his Relativity Theory, but got his Nobel Prize for the Laws of Nature he formulated, the Laws of Photo Effect. Relativity is useless for us to date, but the Laws of Photo Effect gave us light sensors, TV screens, Radars and many other practical things.

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