Answer:
(a)
(b) D. For every unit increase in commute time, the index score falls by <u>0.083</u>, on average.
Step-by-step explanation:
(a)
Form the least-squares regression line using Excel as follows:
Go to Data → Data Analysis → Regression
A dialog box will open.
Select the <em>X</em> and <em>Y</em> variable.
Press Ok.
The regression output is attached below.
The least-squares regression line is:
(b)
The slope of a regression line is the average rate of change in<em> </em>the dependent variable (<em>y</em>) with 1 unit change in the independent variable (<em>x</em>).
Here the slope value is -0.083. This value implies that with 1 minute change in the commute times the Well-Being Index Score falls by 0.083 units.
The intercept of a regression line is the average value of the dependent variable (<em>y</em>) when the independent variable (<em>x</em>) value is 0.
Here, the intercept value is 69.04. This value implies that for a person with commute time 0, their Well-Being Index Score is 69.04.
The correct option is:
D. For every unit increase in commute time, the index score falls by <u>0.083</u>, on average.