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A real estate agency collected the data shown below, where
y = sales price of a house (in thousands of dollars)
x1 = home size (in hundreds of square feet)
x2 = rating (an overall rating for the house expressed on a scale from 1 (worst) to 10 (best).
Sales Price (y) Home Size (x1) Rating (x2)
180.0 23 5
98.1 11 2
173.1 20 9
136.5 17 3
141.0 15 8
165.9 21 4
193.5 24 7
127.8 13 6
163.5 19 7
172.5 25 2
The agency developed the following regression model:
y = βo + β1 x1 + β2 x2+ €
a) Show why this may be a reasonable model for the relationship between the sales price and home size?
b) What factors are represented in the error term in this model? Give a specific example of these factors.
1. Assume the random vector (Trunk Space, Length, Turning diameter) of Japanese car is normally distributed and the unbiased estimators for its mean and variance are the truth. For
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