As an auto insurance risk analyst, it is your job to research risk profiles for various types of drivers. One common area of concern for auto insurance companies is the risk involved when offering policies to younger, less experienced drivers. The U.S. Department of Transportation recently conducted a study in which it analyzed the relationship between 1) the number of fatal accidents per 1000 licenses, and 2) the percentage of licensed drivers under the age of 21 in a sample of 42 cities. Your first step in the analysis is to construct a scatterplot of the data. FIGURE. SCATTERPLOT FOR U.S. DEPARTMENT OF TRANSPORATION PROBLEM U.S. Department of Transportation The Relationship Between Fatal Accident Frequency and Driver Age 4.5 4 3.5 2.5 Fatal accidents per 1000 licenses N 1.5 . . . .. 0.5 0 6 8 10 12 14 16 18 20 Percentage of drivers under age 21visually, 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 The p-value for "Percent under 21" in the regression output is p = 0.0000. The t test for significance in simple linear regression is Ho: B1 = 0 Ha: B1 # 0 Use alpha = .05. What does the p-value tell you about the estimated regression line? O p = 0.0000 indicates that the slope of the estimated regression line is zero, a significant relationship does not exist between the two variables and Ho should not be rejected. O p = 0.0000 indicates that the slope of the estimated regression line is not zero, a significant relationship exists between the two variables, and Ho should be not be rejected. O p= 0.0000 indicates that the slope of the estimated regression line is not zero, a significant relationship exists between the two variables, and Ho should be rejected. O p = 0.0000 indicates that the slope of the estimated regression line is zero, a significant relationship does not exist between the two variables and Ho should be rejected. - Icon Key