4. P (7) = 1 – (0.15 + 0.25 + 0.40) = 0.20.
μ (^) x = 2(0.15) + 6(0.25) + 7(0.20) + 9(0.40) = 6.8.
.
(Remember that this can be done by putting the X -values in L1 , the p (x )-values in L2 , and doing STAT
CALC 1-Var Stats L1,L2 .)
a. The point is both an outlier and an influential point. It is an outlier because it is removed from the
general pattern of the data. It is an influential observation because it is an outlier in the x direction
and its removal would have an impact on the slope of the regression line.
b. Removing the point would increase the correlation coefficient. That is, the remaining data are
better modeled by a line without the box-point than with it.
c. Removing the point would make the slope of the regression line more positive (steeper) than it is
already.