Based on the information given, the thing that can be concluded is that Brand A's data are probably linear while Brand B's data are probably not.
<h3>What is a Linear
regression?</h3>
It should be noted that a linear regression simply shows the relationship between the dependent and independent variables.
If residuals for brand A are randomly scattered above and below the x-axis, and the residuals for brand B are also randomly scattered but clustered closer to the x-axis, it implies that brand A's data are probably linear while Brand B's data are probably not.
A random scatter of points on the residual plot simply implies that there's a linear relationship in the original data set.
Learn more about linear regression on:
brainly.com/question/25987747
I believe it’s 11n -4 -40
8
Because 16 ounces is a pound half of 16 is 8, 8 ounces is half a pound. :)
Answer is a, 57.49.
17.42-12.60-9.62= $-4.80+62.29=57.49
