Answer:
Explanation:
Hello!
Considering the variables:
Y: miles per gallon consumed by a car in the city.
X: the weight of a car.
A sample of n cars was taken and both variables measured.
The correlation coefficient was calculated r= -0.992
And the regression equation ^Y= -0.0073 + 45.2243Xi
The coefficient of determination R² is a sample measurement that determines the percentage or proportion of the variability of the dependent or response variable, Y, that is explained by the independent or explanatory variable, X, in context of the estimated regression model ^Y= a + bXi
Mathematically, the coefficient of determination between two variables is equal to the square of the coefficient of correlation of the same variables.
R²= (r)²
The three questions below are about the coefficient of determination of the linear regression between the miles per gallon and the weight of the car:
1. What proportion of the variability in miles per gallon is explained by the relation between the weight of the car and miles per gallon?
R²= (r)²= (-0.992)= 0.984
2. The proportion of the variability in miles per gallon explained by the relation between the weight of the car and miles per gallon is 98.4%. (Round to one decimal place as needed.)
0.984 * 100= 98.4%
3. Interpret the coefficient of determination. 98.4% of the variance in the miles per gallon consumed by cars in the city is explained by the linear model.
I hope this helps!