Suppose we t a regression line to predict the shelf life of an apple based on its weight. for a particular apple, we predict the shelf life to be 4.6 days. the apples residual is -0.6 days. did we over or under estimate the shelf-life of the apple? explain your reasoning.

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

$4

step-by-step explanation:

$30×5=$150

$150 minus $130=$20

$20÷5=$4.

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b, 20 yards

step-by-step explanation: