In some cases, the true best-fit values for regression parameters may be too large or too small for the calculator to represent accurately. Positive numbers smaller than about 10-300 are rounded to 0, and numbers larger than about 10300 are rounded to infinity.
Very large or very small parameter values can occur in exponential models like or when the x data is far from the origin.
There are two good solutions to this problem:
1. Measure the x data from a baseline that is closer to the collected data. For example, for recent yearly data, measure 'years since 2000' instead of 'years'.
2. Write the exponential model in a different form. Two good choices are or . The parameter c in the latter model has a nice interpretation: it's the x value for which the model predicts a y value of 1. Both of these ways of writing exponential models are less likely to require very large or very small parameter values.