The residual plot for a data set is shown.

based on the residual plot, which statement best explains whether the regression line is a good model for the data set and why?

the regression line is a good model because the points in the residual plot are approximately linear.

the regression line is not a good model because only one point in the residual plot is on the x-axis.

the regression line is a good model because there is a pattern in the residuals.

the regression line is not a good model because the residuals are not randomly distributed.

The regression line is not a good model because the residuals are not randomly distributed.

Step-by-step explanation:

In a regression, the residual is the difference between the observed values and the predicted values.  

If the points in a residual plot are randomly dispersed, a linear regression model is appropriate for the data.

In this case, a pattern is present (the plot is similar to a sine plot); this suggest that a non-linear regression would be better.

yes

step-by-step explanation:

step-by-step explanation:

given that ab is divided into equal parts as

ac, cd, de, ef, fg, gh, hi, ib.

from this we find that f is the midpoint of ab.

so using mid point formula we find

f = (3,7)

similarly considering fb, we get

h = mid point of fb = ((6,6) and g, mid point of fh is

g = (9/2, 13/2)

i is mid point of hb

so i =(15/2,11/2)