Provide a clear solution to the question.
Provide an explanation for your point of view to support your point.
Make sure to describe how your evidence proves your point. Don’t assume it’s obvious.
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, y with logical and on top equals beta subscript 0 plus beta subscript 1 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 following results were obtained:
y with logical and on top = 74.80 + 19.72x
s subscript beta = 71.24, t = 1.05 (for testing beta subscript 0)
s subscript beta = 2.63, t = 7.49 (for testing beta subscript 1)
SSE = 60,775, MSE = 841, s = 29, r squared = 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.
