please show the explanation and solution

3. Performing simple regression analysis with an individual's height {in cm) as the independent variable and their weight (in kg} as the dependent variable. you come up with the following values-.. r2024 r2 = 0.06 v = 0.27:: _ 37.44 Which would be the correct interpretation of the correlation coefcient? r\" 6% of the variability in weight can be explained by the linear relationship between a person's height and their weight. F There is a weak, negative linear relationship between a person's height and their weight. F Each additional 1cm in a person's height leads to increase of 0.2?lrg in their weight. 1"\" 24% of the variability in weight can be explained by the linear relationship between a person's height and their weight. 13" There is a strong, negative linear relationship between a person's height and their weight. 1"\" There is a weak, positive linear relationship between a person's height and their weight. F There is a strong, positive linear relationship between a person's height and their weight. r\" Each additional 1kg in a person's weight leads to increase of 0.2km in their height. 4. Performing simple regression analysis with the the age of a car {in years} as the independent variable and the resale value of the car (in 55) as the dependent variable, you come up with the following values.. r = 43.27 r2 = 0.07 y = 14,233 - 414x Which would be the correct interpretation of the coefficient of determination? F 27% ot the variability in resale value can be explained by the linear relationship between it's age and resale value. r Each additional year in a vehide's age leads to a decrease of $14,233 in its resale value. F There is a strong, negative linear relationship between a vehicle's age and its resale value. If. 7% ofthe variability in resale value can be explained by the linear relationship between it's age and resale value. r. Tit: ofthe variability in age can be explained by the linear relationship between it's age and resale value. Each additional year in a vehicle's age leads to a decrease of $414 in its resale value. There is a weak. negative linear relationship between a vehicle's age and its resale value. r 2?% oi the variability in age can be explained by the linear relationship between it's age and resale value. 5. Performing simple regression analysis with the age of a car (in years) as the independent variable and the resale value of the car (in $) as the dependent variable, you come up with the following values... r = 4185 r2 = 0.73 y = 18,218 -1,212x Which would be the correct interpretation of the regression equation? F Each additional year in a vehicle's age leads to an increase of$1,212 in its resale value. F 73% ot the variability in resale value can be explained by the linear relationship between it's age and resale value. F Each additional dollar in resale value leads to an increase of 1,212 years in its age. F Each additional year in a vehicle's age leads to a decrease of $18,221 8 in its resale value. 5 There is a stmng, negative linear relationship between a vehicle's age and its resale value. F There is a weak, negative linear relationship between a vehicle's age and its resale value. F Each additional year in a vehide's age leads to a decrease of $1,212 in its resale value. r. 85% ot the variability in resale value can be explained by the linear relationship between it's age and resale value