QUESTIDN16 The following regression predicts jail sentence length based on value of property damage, number of victims, and number of character witnesses. Coeffi cient Intercept 5.33 Property Damage Value 0'03 Number of Victims 1,01 Number of Character Witnesses 7036 Using this table, how much would jail sentence change with an additional 1 victim, all else equal? :l QUESTION 17 The following regression predicts life expectancy (how much longer a person is expected to live) based on weekly frequency of alcoholic drinks, Cigarettes smoked' and workouts. Coefcient Intercept 70,96 Drinking Frequency O_62 Smoking Frequency 7029 Workout Frequency 0.38 Using this table, how much would life expectancy change With an additional drink a week, all else equal? QUESTION 18 The following regression predicts income based on years of education, number of children, and years of experience in the job. Coefficient p-value Intercept 35790 0.09 Years of Education 1745 0.03 Number of Children 57 0.57 Years of Experience 936 0.00 Using this table, how much would income change with an additional year of education, all else equal? QUESTION 19 The tables below describe the fit of a regression model. Based on this output, what proportion of the variance in the outcome is explained by the model? Regression Statistics Regression Statistics R Square 0.85 Standard Error 4.77 Observation 692