(Situation N) an Economist Wishes to Study the Monthly Trend $E \left( Y _ { t } \right) = \beta _ { 0 } + \beta _ { 1 } t _ { \text {, where } }$

(Situation N) An economist wishes to study the monthly trend in the Dow Jones Industrial Average (DJIA) . Data collected over the past 40 months were used to fit the model $E \left( Y _ { t } \right) = \beta _ { 0 } + \beta _ { 1 } t _ { \text {, where } }$ , monthly close of the DJIA and $t =$ month $( 1,2,3 , \ldots , 40 )$ . The regression results appear below:
$$\hat { y } = 88 + 0.25 t \quad R ^ { 2 } = 0.37 \quad \text { MSE } = 144 \quad F = 4.25 \quad \text { Durbin-Watson } \mathrm { d } = 0.96$$
-Since the data are recorded over time (months) , there is a strong possibility that the residuals are positively correlated. How could you check for residual correlation using a graphical technique?

A) Plot the residuals against $\hat { y }$ and look for a funnel shape.
B) Plot the residuals against $\hat { y }$ and look for outliers.
C) Plot the residuals against $t$ and look for long runs of positive and negative residuals.
D) Plot the residuals against $\hat { y }$ and look for a linear trend.