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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.
a b c d e supply p 3 4 6 8 8 20 q 2 6 0 5 8 30 r 7 11 20 40 3 15 s 1 0 9 14 6 13 d 15 3 12 10 20
You are given the differential equation dy/dx = y' = f(x, y) with initial condition y(0 ) 1 = . The following numerical method is also given: where f n = f( x n , y n )
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