Answer:
The correct option is;
C. The pattern is random, indicating a good fit for a linear model
Step-by-step explanation:
A graph that has the residuals (the difference between the value observed and the value expected (regression analysis) on the vertical axis and the variable that is not affected by the other variables (independent variable) on the x or horizontal axis is known as a residual plot
A linear regression model is suited in a situation where the points are dispersed randomly on both sides of the horizontal axis
Therefore, given that the first point is below the horizontal axis and the next point is above the horizontal axis, while the third and the fourth points are below the horizontal axis, the fifth, sixth, and seventh points are above the horizontal axis and the eighth point is below the horizontal axis, the points are random around the horizontal axis, indicating the suitability of a linear regression model.
Step-by-step explanation:
(-3y^2+24y)(-6y^2-3y)
open the bracket and collect the like terms
-3y^2-6y^2+24y-3y
-9y^2+21y
P-paratheses (do any math that has parentheses around the numbers) y=(2x5)+25
E-exponents (do the exponents next) y=(2x5)+5^2
M-multiplying. (Basically everything is self explanatory from here to then cuz im lazy to list examples)
Just basically if you don't use PEMDAS, you'll get the wrong answer
The sixth number should be 16 in order for the mean to be 12
