Answer:
Step-by-step explanation:
Given that we fit a regression line to predict the shelf life of an apple based on its weight.
When we fit regression line for a data set , we use least squares concept.
The line which is very nearly fitting the scatter plot is selected in such a ways that the sum of squares of deviations from this line are minimum.
Normally actual value for a particular x and as per line would be different
Residual = Actual y - predicted y as per regression line
Here prediction is 4.6 and residual is -0.6
A residual is negative if actual observed value is less than the predicted value
Hence here we predicted 4 as 4.6 days hence we overestimated the shelf life by 0.6 days
