A local real estate appraiser wants to develop a statistical model to predict the appraised value of properties in a section of the suburb called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Let y = appraised value of the properties (in $thousands) and x = number of rooms. Using data collected for a sample of n = 74 properties in East Meadow, the appraiser fit the following linear regression model:
Appraised Value = 174.80 + 25.80 * Number of rooms
Give a practical interpretation of the estimate of the y-intercept.
Select one:
a. All 74 properties in the sample were worth at least $174,800.
b. For each additional room in the house, we estimate the appraised value to increase $174,800.
c. We estimate that all properties in East Meadow will be expected to have an appraised value of at least $174,800.
d. For each additional room in the house, we estimate the appraised value to increase $25,800.