## Regression model, Applied Statistics

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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.

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