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A local real estate agent is interested in the relationship between the cost of a house ($y$) in dollars and its area ($x$) in square feet. She randomly selects $50$ houses around town and computes the least squares regression line: $\hat { y } =136.89x+14578.91$.

Which of the following is the correct interpretation of the slope of the least squares regression line?

A

For each dollar increase, the estimated square footage of the house increases by $136.89$.

B

For each dollar increase, the estimated square footage of the house increases by $14578.91$.

C

For each additional square foot, the estimated cost of the house increases by $\$136.89$. D For each additional square foot, the estimated cost of the house increases by$\$14578.91$.

E

Since we are not given the $50$ data points, it is impossible to interpret the slope of the least squares regression line in this problem.

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