To find the residual of the data point (1, 16.88), we first need to calculate the predicted value of \( y \) using the given line of best fit, which is:
\[ y = -0.9x + 18.11 \]
Plugging in \( x = 1 \):
\[ y = -0.9(1) + 18.11 \] \[ y = -0.9 + 18.11 \] \[ y = 17.21 \]
Now, the residual is calculated by taking the actual value of \( y \) and subtracting the predicted value of \( y \):
\[ \text{Residual} = \text{Actual } y - \text{Predicted } y \] \[ \text{Residual} = 16.88 - 17.21 \] \[ \text{Residual} = -0.33 \]
So, the residual of the data point (1, 16.88) is \(\boxed{-0.33}\).