.1'5 _ Percent wider 21 Vhich statement offers the best interpretation of the residual plot? 0 0 It appears that the residual plot exhibits a pattern whereby a linear model may not be adequate or the best t, indicating that an assumption of the linear model may have been violated. It appears that the residual plot exhibits a pattern of non-constant variance, indicating that an assumption of the linear model may have been violated. It appears that the residual plot exhibits a good pattern of constant variance, indicating that the equal variance assumption of the model is not supported. It appears that the residual plot exhibits a good pattern of constant variance, indicating that the equal variance assumption of the model is supported. The Relationship Between Fatal Accident Frequency and Driver Age 1.5 4 3.5 W . 2.5 Fatal accidents per 1000 licenses N .. . . 1.5 . .. 0.5 O 6 8 10 12 14 16 18 20 Percentage of drivers under age 21 Upon visual inspection, you determine that the variables do have a linear relationship. After a linear pattern has been established visually, you now proceed with performing linear regression analysis. The results are as follows: TABLE. LINEAR REGRESSION OUTPUT FOR U.S. DEPARTMENT OF TRANSPORTATION PROBLEM Coefficients Standard Error t Statistic p-value Intercept -1.5974 0.3717 -4.2979 0.0001 Percent Under 21 0.2871 0.0294 9.7671 0.0000 final step in regression analysis is an examination of the residuals in a residual plot. This allows you to test the assumptions of the egression model itself by looking for patterns in the residuals. The residual plot for the problem is as follows