Question

what does a residual value of 1.3 mean when referring to the line of best fit of a data set? a data point is 1.3 units below the line of best fit. a data point is 1.3 units above the line of best fit. the line of best fit has a slope of 1.3. the line of best fit has a slope of -1.3.

Explanation:

The residual is calculated as the actual value minus the predicted value (from the line of best fit). A positive residual means the actual data point (y - value) is greater than the predicted value, so the data point is above the line of best fit. A residual of 1.3 is positive, so the data point is 1.3 units above the line. The slope of the line of best fit is not related to the residual value, so the options about the slope are incorrect. The option about being below would correspond to a negative residual.

Answer:

B. A data point is 1.3 units above the line of best fit. (Note: Assuming the second option is labeled B as per typical multiple - choice formatting where the first is A, second B, etc. If the original options had different labels, adjust accordingly, but based on the given options, the correct description is "A data point is 1.3 units above the line of best fit".)