The Correlation Coefficient:
In the first part of this tutorial, we saw how to use the trendline feature in Excel to fit a straight line through calibration data and obtain both the equation of the best-fit straight line and the correlation coefficient, R (often reported as R2). There are in fact various correlation coefficients, but the one we are interested in here is the Pearson or product-moment correlation coefficient. The Pearson R value provides a measure of the degree to which the values of x and y are linearly correlated. We can assess this visually using a scatter plot (Figure 1), in which we also mark the centroid of the data, .
Figure 1 - XY scatter plot showing the centroid of the data