Professor does not teach from a book so am not sure how to apply this problem to the regression equation.
Thanks in advance. Problem below.
Cell Phone Mins= 3.5*cost + 25
where cell phone mins measure the number of minutes per month and cost is the dollar amount paid for the cell phone.
A) How many cell phone minutes are estimated to be used for someone who paid $95 for the cell phone?
B) Interpret the slope coefficient as an elasticity.
Regression equation can be stated in this form:
predicted y = a + bx
...where 'a' is the intercept and 'b' is the slope.
Therefore, for part A, substitute 95 for 'cost' and solve for 'cell phone minutes' in the equation given.
For part B, use 3.5 for the slope to determine elasticity.
Hope this will help get you started.
Thanks so much. I was on the right track then.
To apply the given problem to the regression equation, you can use the equation provided:
Cell Phone Mins = 3.5 * cost + 25
This equation represents a linear regression model, where the number of cell phone minutes is predicted based on the cost of the cell phone.
A) To find the number of cell phone minutes estimated for someone who paid $95 for the cell phone, you substitute the given cost value into the equation and solve for the number of minutes:
Cell Phone Mins = 3.5 * $95 + 25
Cell Phone Mins = $332.5 + 25
Cell Phone Mins = $357.5
Therefore, it is estimated that someone who paid $95 for the cell phone will use approximately 357.5 minutes.
B) To interpret the slope coefficient (3.5) as an elasticity, you need to understand that elasticity represents the percentage change in one variable in response to a one percent change in another variable. In this case, the slope coefficient (3.5) represents the change in cell phone minutes for a one unit change in cost.
So, the interpretation of the slope coefficient as an elasticity would be that for every one dollar increase in cost, the number of cell phone minutes is estimated to increase by 3.5 minutes.
This means that the relationship between the cost and the number of cell phone minutes is positive, suggesting that as the cost of the cell phone increases, the predicted number of minutes used also increases.