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What does a residual value of -0.8 mean in reference to the line of best fit?

A. The given point is 0.8 units above the line of best fit.
B. The given point is 0.8 units below the line of best fit.
C. The line of best fit is not appropriate to the data.
D. The line of best fit has a slope of 0.8.

Sagot :

GinnyAnsweridn
A residual value measures the difference between an observed value and the corresponding predicted value on the line of best fit.

The residual is calculated as:
[tex]\[ \text{Residual} = \text{Observed value} - \text{Predicted value} \][/tex]

If the residual is negative, this implies that the observed value is less than the predicted value provided by the line of best fit.

Given a residual value of -0.8:
[tex]\[ -0.8 = \text{Observed value} - \text{Predicted value} \][/tex]
This indicates that the observed value is 0.8 units below the predicted value (below the line of best fit).

Therefore, a residual value of -0.8 means that the given point is 0.8 units below the line of best fit. Thus, the correct answer is:

The given point is 0.8 units below the line of best fit.
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