Refer to the IHS Journal of Hydraulic Engineering (September 2012) study of water pipes susceptible to breakage, Exercise 10.31. Recall that civil engineers used simple linear regression to model y = the ratio of repair to replacement cost of commercial pipe as a function of x = the diameter (in millimeters) of the pipe. Obtain the regression residuals and construct two graphs: (1) a plot of the residuals against diameter of the pipe, and (2) a normal probability plot. What do these plots suggest about the validity of the assumptions on the random error term?

**Data from Exercise 10.31**

Refer to the IHS Journal of Hydraulic Engineering (September 2012) study of water pipes susceptible to breakage, Exercise 10.8. Recall that civil engineers used simple linear regression to model y = the ratio of repair to replacement cost of commercial pipe as a function of x = the diameter (in millimeters) of the pipe. Are the engineers able to conclude (at α = .05) that the cost ratio increases linearly with pipe diameter? If so, provide a 95% confidence interval for the increase in cost ratio for every 1 millimeter increase in pipe diameter.

**Data from Exercise 10.8**

Pipes used in a water distribution network are susceptible to breakage due to a variety of factors. When pipes break, engineers must decide whether to repair or replace the broken pipe. A team of civil engineers used regression analysis to estimate y = the ratio of repair to replacement cost of commercial pipe in the IHS Journal of Hydraulic Engineering (September 2012). The independent variable in the regression analysis was x = the diameter (in millimeters) of the pipe. Data for a sample of 13 different pipe sizes are provided in the table.