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
s
β = 71.24, t = 1.05 (for testing β
0)
s
β = 2.63, t = 7.49 (for testing β
1)
SSE = 60,775, MSE = 841, s = 29, r
2 = 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.
Model Organism Neurospora
Media Practice Model
Develop a Patient Teaching Handout About Stress
An Alternative Model of Global Stratification
How the Wernicke-Geschwind model works in a person who is responding to a heard question and reading ...
An additive model for the inheritance of height in the Potsdam Guards. In this example, the guards a