## Power Regression

The power regression option finds the equation of
the form y = ax^{b} that best fits a set of data.
Press to
choose the statistics application. Choose `fit data...`

and press
.
Enter the data.

The values of x and y must be greater than zero. (This is because the method for determining
the values of a and b in the regression equation is a least-squares fit on the
values for ln x and ln y.)

The data shown here are the points {(2,11.4), (3,17), (5,27.3), (7,36.1), (11,47.7), (13,49.9)}.

Press
to choose a statistics calculation option.

Select `Power Fit`

and press .

Press to calculate the regression.

The regression equation is in level 3 of the stack, the correlation in level 2, and
covariance in level 1. To view the entire correlation press
. Press
again to see the regression equation itself.

Therefore, the best-fit power equation for this data is approximately
y = 7.01x^{0.8}.