To find the residual of the data point (1, 16.88) given the line of best fit \( y = -0.9x + 18 \), we first need to calculate the y-value predicted by the line of best fit for \( x = 1 \).
- Plug \( x = 1 \) into the equation to find the predicted y-value:
\[ y = -0.9(1) + 18 \] \[ y = -0.9 + 18 \] \[ y = 17.1 \]
-
The actual y-value from the data point is 16.88.
-
The residual is calculated as:
\[ \text{Residual} = \text{Actual} - \text{Predicted} \] \[ \text{Residual} = 16.88 - 17.1 \] \[ \text{Residual} = -0.22 \]
So, the residual of the data point (1, 16.88) is \(-0.22\).
Rounding to the nearest hundredths, the final answer is:
\[ \boxed{-0.22} \]