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spruckj spruckj
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Posts: 435
5 years ago
Provide an appropriate response.

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 houses in East Meadow, the following results were obtained:
     = 74.80 + 19.72x
     sβ  = 71.24, t = 1.05 (for testing β0)
     sβ  = 2.63, t = 7.49 (for testing β1)
     SSE = 60,775, MSE = 841, s = 29, r2 = 0.44
     Range of the x-values: 5 - 11
     Range of the y-values: 160 - 300
Give a practical interpretation of the estimate of the y-intercept of the least squares line.

▸ For each additional room in the house, we estimate the appraised value to increase $19,720.

▸ We estimate the base appraised value for any house to be $74,800.

▸ There is no practical interpretation, since a house with 0 rooms is nonsensical.

▸ For each additional room in the house, we estimate the appraised value to increase $74,800.
Textbook 
Statistics: Informed Decisions Using Data

Statistics: Informed Decisions Using Data


Edition: 5th
Author:
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tlastertlaster
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Posts: 402
5 years ago
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