The exponential fit data derived from an exercise involving a bouncing ball. A high bounce ball was dropped from 100 centimeters and the height of the nth bounce was recorded.
| Bounce | Height |
| 0 | 100 |
| 1 | 75 |
| 2 | 63 |
| 3 | 40 |
| 4 | 37 |
| 5 | 26 |
| 6 | 19 |
| 7 | 12 |
| 8 | 10 |
| 9 | 8 |
| 10 | 5 |
For the bouncing ball problem, the height of each subsequent bounce is a percentage of the previous bounce. Thus the function is a multiplication of the percentage bounce or f(x) = (percentage)^x. LibreOffice.org Calc does a nice job of finding this function for the data.
In the above chart the ball is bouncing to a height of 74% of the previous bounce.When one attempts to create the same chart in Microsoft Excel 12 (Excel 2007), the result is a mathematically equivalent but less scientifically satisfactory exponential decay using the base e.
While mathematically equivalent, a base e function does not directly reveal the percentage value. One has to calculate e^(-0.30). Thus e^-0.30 ≈ 0.74, at least to within the rounding error.
Another difference between the Calc and Excel is that LibreOffice.org Calc ran a vbest fit using a power function on the original data. LibreOffice.org automatically discarded the mathematically problematic x = 0 value.
Microsoft Excel balked. A new table had to be constructed without the x = 0 value for Excel to proceed. One could argue that this is a preferred behavior: Excel is making no mathematical decisions without being explicitly told to do so. I, however, prefer the Calc approach. If I want a power function then I ought to already know that 0^-n ≠ 100, that the function is undefined at x = 0.




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