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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 ran the multiple regression. 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?

Sagot :

Parrain

When analyzing the multiple regression model, the real estate builder should be concerned with Multicollinearity.

What is Multicollinearity?

This is a phenomenon in regression analysis where some of the independent variables are correlated. This can present an issue because the correlation leads to less reliable results.

The income in this research is influenced by the education and they both influence family size. There is therefore an issue of multicollinearity here because some variables are correlated.

Find out more on Multicollinearity at https://brainly.com/question/16021902.

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