Answer
Yes, the point (1906, 4625) is an outlier and influential observation.
Work Step by Step
See the scatter diagram in item 3 (a). Observe how far the point (1906, 4625) is from the other points corresponding to the observations for Nassau County.
Let's remove this point point from the data and find a new least-squares regression line:
In MINITAB, enter the square footage values for Nassau County in C1 and in C2 enter the rent per month values for Nassau County (do not forget to remove the observation in which the square footage is 1906 and rent per month is 4625).
Select Stats -> Regression -> Regression -> Fit Regression Model
Enter C2 in "Responses" and C1 in "Continuous Predictors"
The least-squares regression line ($ŷ =b_1x+b_0$) will be shown in "Regression Equation", where C2 is ŷ (rent per month) and C1 is x (square footage)
$ŷ =0.878x+675$
We can conclude that this observation is also influential because the both the slope and the y-intercept have changed substantially.
