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)Randomness of error terms
B)Collinearity
C)Normality of residuals
D)Missing observations

Question

Quizplus · Accepted Answer

The real estate builder should be particularly concerned with collinearity because education is a predictor for both income and family size, which may result in high multicollinearity in the model. This can affect the accuracy and interpretation of the coefficients and make it difficult to determine the separate effects of each predictor variable.

A Real Estate Builder Wishes to Determine How House Size