Linear Regression Analysis (Least Squares Method)

. In preparing a calibration plot expected to be linear, significantly better accuracy may be obtained by using a least squares analysis. By using the least squares method a better fit of a straight line and a more accurate slope and intercept can be obtained. The Excel program will complete the tedious least squares mathematical routine for you and allow you to plot both your original data points as well as a projected "best-fit" line. We will also use the Regression Analysis Tool to determine the slope and intercept of the "best-fit" straight line through our data.

Using appropriate x and y scales, axis labels, units and title a scattered plot of the data below. On the same plot, add the linear regression equation and the correlation coefficient, R².

Calibration Data for Beer's Law
Molarity (M)	Absorbance (a.u.)
0.0065	0.0540
0.0190	0.2105
0.0250	0.4787
0.0354	0.6898
0.0459	0.9888

Now, answer the questions below using the plot you generated.

What is the concentration of this solution that has an absorbance of 0.3200 a.u.?

M

What would be the expected absorbance of a 0.0650 M solution under the same conditions?