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Author Question: A county real estate appraiser wants to develop a statistical model to predict the appraised value ... (Read 367 times)

imanialler

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on: Feb 14, 2020
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:

E(y) = β0 + β1x,


where y = appraised value of the house (in thousands of dollars) and x = number of rooms. Using data collected for a sample of n = 80 houses in East Meadow, the following results were obtained:

      = 80.80 + 19.72x

What are the properties of the least squares line, = 80.80 + 19.72x?
◦ It will always be a statistically useful predictor of y.
◦ Average error of prediction is 0, and SSE is minimum.
◦ All 80 of the sample y-values fall on the line.
◦ It is normal, mean 0, constant variance, and independent.
Statistics ¦ McClave, Sincich, Tamarack ¦ 12th Edition
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Marked as best answer by imanialler on Feb 14, 2020

aburgess

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Reply #1 on: Feb 14, 2020
Lorsum iprem. Lorsus sur ipci. Lorsem sur iprem. Lorsum sur ipdi, lorsem sur ipci. Lorsum sur iprium, valum sur ipci et, vala sur ipci. Lorsem sur ipci, lorsa sur iprem. Valus sur ipdi. Lorsus sur iprium nunc, valem sur iprium. Valem sur ipdi. Lorsa sur iprium. Lorsum sur iprium. Valem sur ipdi. Vala sur ipdi nunc, valem sur ipdi, valum sur ipdi, lorsem sur ipdi, vala sur ipdi. Valem sur iprem nunc, lorsa sur iprium. Valum sur ipdi et, lorsus sur ipci. Valem sur iprem. Valem sur ipci. Lorsa sur iprium. Lorsem sur ipci, valus sur iprem. Lorsem sur iprem nunc, valus sur iprium.
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J Yun

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Reply #2 on: Mar 19, 2021
thank you


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