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 in years. The builder randomly selected 50 families and constructed the multiple regression model. The business literature involving human capital shows that education influences an individual's annual income. Combined, these may influence family size. With this in mind, what should the real estate builder be particularly concerned with when analyzing the multiple regression model?
A) Missing observations B) Collinearity
C) Normality of residuals D) Randomness of error terms
Question 2
In a multiple regression model, which of the following is correct regarding the value of the adjusted r2?
A) It can be negative.
B) It has to be larger than the coefficient of multiple determination.
C) It can be larger than 1.
D) It has to be positive.
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