Question

Insurance companies use special (actuarial) tables to estimate the remaining lifespan of their customers. Below is the regression model estimating the additional years left for American males in the United States, according to a National Vital Statistics Report. The regression equation is: Years Left =60.5−0.62 (Age) R-Squared ( R 2 )=96%

(a) What is the slope?
−0.62
−0.635
60.2
0.62
60.5
​

Answer 1

The slope of the regression equation 'Years Left = 60.5 - 0.62 (Age)' is -0.62, which means for every year increase in age, the estimated remaining years left decrease by 0.62. This regression model with an R-Squared value of 96% shows a strong linear relationship between age and estimated years left to live.

Step-by-step explanation:

The slope in the regression equation Years Left = 60.5 - 0.62 (Age) represents the change in the dependent variable (Years Left) for each one-unit change in the independent variable (Age). In this case, the slope is -0.62, which means that for every additional year of age, the estimated remaining years left decrease by 0.62. This slope was determined using actuarial tables which help insurance companies estimate the life expectancy of their customers. The R-Squared value of 96% indicates that the regression model explains 96% of the variability in the life expectancy based on age, which implies a strong linear relationship between age and years left to live.