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 metres,income is measured in thousands of dollars,and education is in years.The builder randomly selected 50 families and developed a 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 analysing the multiple regression model?
A)Normality of residuals.
B)Collinearity.
C)Missing observations.
D)Randomness of error terms.

Question

Quizplus · Accepted Answer

The real estate builder should be particularly concerned with collinearity, as education may be highly correlated with both income and family size. This can cause issues in the regression model, leading to unreliable coefficient estimates and difficulty in interpreting the results. Normality of residuals, missing observations, and randomness of error terms are important considerations in any regression analysis, but they are not specifically related to the issues that may arise from collinearity.

A Real Estate Builder Wishes to Determine How House Size