Suppose a bank would like to develop a regression model to predict a person\'s c

Question

Suppose a bank would like to develop a regression model to predict a person's credit score based on his or her age, weekly income, highest education level (high school, bachelor degree, graduate degree), and whether or not he or she owns or rents his or her primary residence. The accompanying table provides these data for a random sample of customers. Complete parts a through d below. E Click the icon to view the data table. a. Using technology, construct a regression model using all of the independent variables. (Let variable Ed1 be one of the dummy variables for the education level. Assign a 1 to a bachelor degree for this variable. Let Ed2 be another dummy variable for the education level. Assign a 1 to a graduate degree for this variable. Also, let variable Res be the dummy variable for the Residence variable. Assign a 1 if the person owns his or her primary residence.) Complete the regression equation for the model below, where y= Credit Score, x,-Income. x2-Age, X3-Ed1. x4-Ed2, and X5-Res 4705200x192(4785x(8332 (42 42 %s Round to twn derimal nlares as needed

Explanation / Answer

We cannot get a graduate degree without a bachelor degree so option B provides the correct hierarchichal interpretation.

Coefficient of x3 denotes the average increase in credits due to Bachelor degree.Hence answer to part 1 is 47.85.

Coefficient of x4 indicates the average increase in credits due to Graduate degree which is 83.32.At last primary residence increases average credits by coefficient of x5 i.e 42.42

Related Questions

Navigate

• Browse (All)
• Browse S
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.