The linear regression option finds the equation of a linear equation of
the form y = ax + b that best fits a set of data.
enter the data .
to view the statistics calculation options.
Enter the columns to be used for the x and y entries, c1 and c2 in this case.
The regression equation can be automatically stored in the equation editor by selecting
the Stor RegEQ.
The resulting equation is y = 0.24x + 1.14. The TI-92 calculates the correlation
coefficient, r. In this case, r is about 0.91.
The value of r lies between -1 and 1, inclusive. It is a measure of how well the
regression equation fits the data.
A value of -1 or 1 indicates a perfect fit. The TI-92 also calculates the correlation
of determination, R2.
Note: The resulting linear equation is an exact fit if two nonvertical data points
See Appendix B in the
Precalculus: Making Connections for information on the value of the correlation
coefficient and the value of the coefficient of determination.