A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county 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 . Consequently , the appraiser decided to fit the simple linear regression model where y = appraised value of the house (in $thousands ) and x = number of rooms. Using data collected for a sample of 74 houses in East Meadow , the following results were obtained hat y =19.72x+75.8 Give a practical interpretation of the estimate of the y- intercept of the least squares line .

We estimate the base appraised value for any house to be $75,800.

There is no practical interpretation, since a house with rooms is nonsensical.

For each additional room in the house, we estimate the appraised value to increase $19.720.

For each additional room in the house, we estimate the appraised value to increase $75,800.