Linear Regression

The linear regression option finds the equation of a linear equation of the form y = ax + b that best fits a set of data. First, press to enter the data .

Press to view the statistics calculation options.

Press .

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 are entered.

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.