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 10^{300} 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:

- 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'. - 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.

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