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multiple regression model

A real estate builder wishes to determine how house size (house) is influenced by family income (income), family size (Size) and education of the head of household (School) . House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is measured in years. The builder randomly selected 50 families and ran the mutiple regression. The business literature invoving human capital shows that education influences an individual's annual income. Combined these may influence family size. WIth this in mind what should real estate builder be particularly concerned with when analyzing the mutiple regression model?

A. Randomness of error terms
B. Collinearity
C. Normality of Residuals
D. Missing obserseervations

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Hello

The regression equation as mentioned in the situation is

House = alpha1 + beta1*income + beta2*size + beta3*school + error terms eq(1)

The dependent variable is house and independent variables are income, size, and school

However ...

Solution Summary

Solution shows an answer of a multiple choice question.

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