Question

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, ? = ?? + ??x, where y = appraised value of the house (in $thousands) and x = number of rooms. Using data collected for a sample of n = 74 houses in East Meadow, the accompanying results were obtained. Give a practical interpretation of the estimate of the y-intercept of the least squares line. Click the icon to view the results. A. There is no practical interpretation, since a house with 0 rooms is nonsensical. B. The base appraised value for any house is estimated to be $74,800. C. For each additional room in the house, the appraised value is expected to increase $74,800. D. For each additional room in the house, the appraised value is expected to increase $19,720.

          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, ? = ?? + ??x, where y = appraised value of the house (in $thousands) and x = number of rooms. Using data collected for a sample of n = 74 houses in East Meadow, the accompanying results were obtained. Give a practical interpretation of the estimate of the y-intercept of the least squares line.
Click the icon to view the results.

A. There is no practical interpretation, since a house with 0 rooms is nonsensical.
B. The base appraised value for any house is estimated to be $74,800.
C. For each additional room in the house, the appraised value is expected to increase $74,800.
D. For each additional room in the house, the appraised value is expected to increase $19,720.

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, ? = ?? + ??x, where y = appraised value of the house (in thousands) and x = number of rooms. Using data collected for a sample of n = 74 houses in East Meadow, the accompanying results were obtained. Give a practical interpretation of the estimate of the y-intercept of the least squares line.
Click the icon to view the results.

A. There is no practical interpretation, since a house with 0 rooms is nonsensical.
B. The base appraised value for any house is estimated to be74,800.
C. For each additional room in the house, the appraised value is expected to increase 74,800.
D. For each additional room in the house, the appraised value is expected to increase19,720.

Added by Michael J.

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