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Mathematics
General Math
How can we accurately model data using curve fitting techniques?
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[QUOTE="jedishrfu, post: 5574179, member: 376845"] We know that when you hang a chain you get a catenary. We also know that you can approximate a catenary within a given domain using a polynomial. You were approaching the problem from the measurement end to get your polynomial and that's where you have to stop. You have no theory to explain the polynomial fit or why you came up with a polynomial. This happens a lot in science where the data is neatly described by a polynomial but there's no theory to explain it. In one example, Cornell Univ folks had developed an AI that could discern the equations of motion from data about a compound pendulum and the equations were spot on. However later a biology team used the same program to analyze some cell data and once again they got a equation that was spot on but they couldn't publish because they couldn't explain the equation from theory. In contrast, the catenary comes from analyzing the nature of the hanging chain and deriving the catenary from that analysis. [/QUOTE]
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How can we accurately model data using curve fitting techniques?
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