The residual of a data point is calculated as the difference between the actual value and the predicted value given by the line of best fit.
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Given data:
- The line of best fit: \( y = -0.9x + 18 \)
- The actual data point: \( (1, 16.88) \)
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Calculate the predicted value when \( x = 1 \): \[ y_{\text{predicted}} = -0.9(1) + 18 = -0.9 + 18 = 17.1 \]
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Find the residual: \[ \text{Residual} = \text{Actual value} - \text{Predicted value} = 16.88 - 17.1 \] \[ \text{Residual} = -0.22 \]
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Round the answer to the nearest hundredths: \[ \text{Residual} = -0.22 \]
Thus, the residual of the data point (1, 16.88) is -0.22.