The correlation coefficient of a regression line is a measure of how closely the line fits our data. Negative correlation coefficients represent decreasing lines; positive correlation coefficients represent increasing lines.
The closer a correlation coefficient is to +1 or -1, the better the fit; a perfect positive fit is r=1 and a perfect negative fit is r=-1.
We can see in the graph that the line is very close to our data, so it is a pretty good fit.
The line is increasing; this means we want a correlation coefficient that is close to 1.
