A regression equation that predicts the price of homes in thousands of dollars i

Question

A regression equation that predicts the price of homes in thousands of dollars is t = 24.6 + 0.055x1 - 3.6x2, where x2 is a dummy variable that represents whether the house in on a busy street or not. Here x2 = 1 means the house is on a busy street and x2 = 0 means it is not. Based on this information, which of the following statements is true? And why?

a) On average, homes that are on busy streets are worth $3600 less than homes that are not on busy streets.

b) On average, homes that are on busy streets are worth $3.6 more than homes that are not on busy streets.

c) On average, homes that are on busy streets are worth $3.6 less than homes that are not on busy streets.

d) On average, homes that are on busy streets are worth $3600 more than homes that are not on busy streets.

Explanation / Answer

As the slope of 2 is negative, then the cost is higher for houses on non-busy streets.

As the unit of t is in thousands, then we multiply -3.6 by 1000, so -3600 for a change from x2 = 0 to x2 = 1.

Hence,

OPTION A: a) On average, homes that are on busy streets are worth $3600 less than homes that are not on busy streets. [ANSWER]

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