A local real estate company wants to better understand the housing market in the Bethesda/Rockville area. The company hires you to do some analysis. Suppose that you have collected information on the selling price of 218 houses that are randomly selected from recent transactions. You compute the sample mean of these prices to be Y-bar = $1,006,670 and the sample standard deviation to be s = $172,400.
A friend of yours is shopping for a house and is interested in a particular three-bedroom house in Bethesda, which is 7 years old and has 1,750 square feet of gross living pace. The asking price for the house is $1,000,000. Using the regression model, would you say the asking price is higher or lower than its fair market value, in the absence of any additional information?

A) Higher than the marketbecause the model predicts around $ 933,268
B)Higher than the marketbecause the model predicts around $ 834,326
C)Higher than the marketbecause the model predicts around $ 924,619
D)Lower than the marketbecause the model predicts around $1,038,677
E)We can't predict the pricewith these numbers but all indications are that it is lower than market

Summary Measures

Mean

1006697.2

Std Dev

172398.99

Std Err Mean

11676.333

upper 95% Mean

1029710.8

lower 95% Mean

983683.71

N 218
 

00000 900000 11000001300000