Thanks to your comment, I was able to calculate the values of DFFITS and DFFBETAS using PROC IML and PROC REG. I'm very grateful. The calculation of each of the elements used in the formulas for calculating these statistics has enabled me to understand the reasons why an observation which, like the outlier in my data, is not influential in the sense of "modifying the slope of the regression line very much", has a higher DFBETAS than the observation below the rest of the scatter plot, which is clearly influential. I conclude from this that, if the aim is to discard the few observations that have an exaggerated influence on the estimated value of the slope, while keeping the outliers that, located in the extension of the regression line, contribute to the significance of the estimated value of the slope, I must not rely on the highest absolute values of DFBETAS. But maybe I'm wrong. I'd like to hope so.