Step-by-step explanation:
quantitative variables are any variable where the data represent amount . for example height ,weight or age.
categorical variables are any variable where the data represent group. for example eye colour.
the best way to represent data by frequency table,pie chart and bar chart.
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
<span>2r ≤ 3(2r - 7)
</span><span>2r ≤ 6r - 21
</span><span>21 ≤ 6r - 2r
</span><span>21 ≤ 4r
</span><span>21/4 ≤ r
r</span>
21/4
r
5.25
Answer:
Step-by-step explanation:
