Hi Robert,
OK,
now I know what you meant by R^2!!
I typically don't rely on the R^2 value for curve fit comparisons, since it favors numbers that are larger in value.
When I did the coast down testing analysis, I noticed that the example at the Instructables used the R^2 technique, and again, it puts more emphasis on larger velocities during the coast down test, than the smaller one's close to zero miles per hour.
Rather, I like to calculate the difference between the curve fit and raw data in percent. This technique gives equal footing between the smaller numbers in the data set and the larger one's. So if I'm trying to come up with a good curve fit for some raw data, the percentage method gives the entire curve the same emphasis, and not skew the deviation towards the larger numbers at higher speeds.
I have included this approach in the table below, so you can see how accurate the curve fit is for our template in question.
Note: one should not be alarmed by the large error at the smaller X-Axis distances. It should be easy to either curve fit the lower data over a smaller range, or make a template in foam, then smooth the transitions using the eye-ball method.
