Below are the scatter plot and residual plot for a set of data. A linear model
(is/is not)

the best fit for the data because the residual plot
(shows no pattern/shows a pattern)

and is
(scattered/not scattered)​

A linear model (is/is not) the best fit for the data because the residual plot (shows no pattern/shows a pattern) and is (scattered/not scattered).

Step-by-step explanation:

A linear model should be used when you want to view the data as a continuous response. This means that when the data is increasing/describing then the line should be in a uniform pattern.

If you were to look at the residual plot, you can see that the points curve in a pattern, meaning that the point is not scattered which is not good criteria for a residual plot.

Mentioned before, the points on the residual plot are in a pattern, so it’s not scattered as well.  

b) the dogs need to shift their focus to human scent.