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
Answer:
20 is the LCM of 5 and 20.
....
The average can be calclculated as follows:
average = sum of number/number of numbers
average = (19+45) / 2 = 64/2 = 32
10w + 9 Are you combing like terms?
