The following output summarizes the fit of an analysis of covariance to the data in Exercise 35. The variable  denotes a dummy variable, with  for values colored green and 0 otherwise. (a) Does the...

The following output summarizes the fit of an analysis of covariance to the data in Exercise 35. The variable
 denotes a dummy variable, with
 for values colored green and 0 otherwise.

(a) Does the fit of the model suggest parallel equations for the two groups?

(b) How would the output change if the coding of the dummy variable
 were reversed (so that 0s became 1s and vice versa)?

(c) What should be the next step in analyzing these data, specifically thinking of the form of the fitted model?

Exercise 35

The analysis of covariance emphasizes the use of regression to fix a problem with the two-sample
-test that has a confounding variable. You can also think of the use of a dummy variable as a way to fix a problem in the regression of
 on
. Take a look at this scatter-plot:

(a) If we fit parallel slopes to these data, with one line for the red and another for the green points, what do you think the slope will be?

(b) What happens if we estimate the slope while ignoring the presence of two clear groups? That is, if we fit a simple regression of
 on
 using all of the data?