A consumer protection group compares three types of front bumpers for a brand of automobile. A test is conducted by driving an automobile into a concrete wall at 15 miles per hour. The response is the amount of damage to the car, as measured by the repair costs, in hundreds of dollars. Due to the potentially large cost, the study conducts only two tests with each bumper type. The following table shows the results. Bumper A Bumper B Bumper C 11 2 3 14 15 a. Use the attached ANOVA SAS output to determine if at the significance level of 0.1 the bumpers are different. b. If the differences are significantly different, use Tukey's method to see which groups are different.The GLM Procedure Dependent Variable: Cost Sum of Source DF Squares Mean Square F Value Pr > F Model 2 148.0000000 74.0000000 18.50 0.0205 Error 3 12.0000000 4.0000000 Corrected Total 5 160.0000000 R-Square Coeff Var Root MSE Cost Mean 0.925000 33.33333 2.000000 6.000000 Source DF Type I SS Mean Square F Value Pr > F Group 2 148.0000000 74.0000000 18.50 0.0205 Source DF Type III SS Mean Square F Value Pr > F Group 2 148.0000000 74.0000000 18.50 0.0205The GLM Procedure Tukey's Studentized Range (HSD) Test for Cost NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type II error rate than REGWQ. Alpha 0.1 Error Degrees of Freedom Error Mean Square Critical Value of Studentized Range 4.46734 Minimum Significant Difference 6.3178 Cost Tukey Grouping for Means of Group (Alpha = 0.1). Means covered by the same bar are not significantly different. Group Estimate 13.0000 3,0000 2.0000