appraiser Wa to predi appra 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: E(y) = Bo + Bix, where y = appraised value of the house (in thousands of dollars) and x = number of rooms. Using data collected for a sample of n = 73 houses in Fast Meadow, the following results were obtained: y = 73.80 + 19.72x What are the properties of the least squares line, y = 73.80 + 19.72x? A) Average error of prediction is 0, and SSE is minimum. B) It will always be a statistically useful predictor of y. C) It is normal, mean 0), constant variance, and independent. D) All 73 of the sample y-values fall on the line.

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)A county real estate appraiser wants to develop a statistical model to predict the appraised value of 3)
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:
E(u) = Bo + Bix,
where y = appraised value of the house (in thousands of dollars) and x = number of rooms. Using data
collected for a sample of n = 73 houses in Fast Meadow, the following results were obtained:
y = 73.80 + 19.72x
What are the properties of the least squares line, y = 73.80 + 19.72x?
A) Average error of prediction is 0, and SSE is minimum.
B) It will always be a statistically useful predictor of y.
C) It is normal, mean 0, constant variance, and independent.
D) All 73 of the sample y-values fall on the line.
Transcribed Image Text:)A county real estate appraiser wants to develop a statistical model to predict the appraised value of 3) 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: E(u) = Bo + Bix, where y = appraised value of the house (in thousands of dollars) and x = number of rooms. Using data collected for a sample of n = 73 houses in Fast Meadow, the following results were obtained: y = 73.80 + 19.72x What are the properties of the least squares line, y = 73.80 + 19.72x? A) Average error of prediction is 0, and SSE is minimum. B) It will always be a statistically useful predictor of y. C) It is normal, mean 0, constant variance, and independent. D) All 73 of the sample y-values fall on the line.
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