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:

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.

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