Leverage is a statistic which measures how influential each observation is in determining the coefficients of the estimated model. In this case, an average data point would have a leverage value equal to 0.15384615384615385. There is one data point with more than 3 times the average leverage, but none with more than 5 times. Obviously, we want to answer the question of whether a criterion value is unusual with respect to the model we are using. Residuals look at differences between the model and the criterion value.
Raw residuals have two major problems.
Studentized deleted residuals solve both of these problems. On the left you see an applet where two regression lines are drawn. As you move the data values along the y-axis, the blue regression line is formed using all nine values, while the magenta regression line is formed using only the first eight values. On the far right of the applet two different residual values are plotted. Note how these two residuals can be drastically different from one another.