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However, there is still a problem as one error (predicted age minus actual age) might be 10 years and another might be −10 years, then adding 10 (−10) = 0 one has a perfect fit—but not really, for both are off by 10 years.

Mathematicians get around this by the method of least squares where one finds the values of A, B, and C that will yield the smallest total of the squares of the errors, here 102 (−10) = 100 100 = 200.

Least squares curve fitting will be used to find the best values of A, B, and C.

Data will be stored in the form (x represents the life span of the person.

Suppose a certain town has 1000 people and is growing at 10% a year.

In a year it will have 1000 plus 10% of 1000, which is 100, residents and 1000 100 = 1100.

Another very famous number, but only with those who study mathematics, is e which is approximately 2.718. Dividing the 10% yearly growth between the 12 months, each month the town would grow 10%.

As the lifespans of people born after the Flood are generally decreasing, one expects an exponential decay curve—like the town that is losing 10% a year (y = 1000e) will have a negative B value. ) It was apparent from the start that one needed an equation of the form y = Ae C, with B less than called an exponential growth or exponential decay curve, depending on whether B is positive or negative.This is crucial to the understanding of this paper, so a few words need to be spent for the benefit of those who are not mathematicians.The numbers given in the various texts of the Scriptures will be taken at face value.Others can worry about the validity of the numbers.