Question 8 (3 points) Saved The following is a regression of credit scores based on an individual's age, income, their location (whether they are in the North, South, East or West part of the U.S.) and whether they are a female or a male. The location dummies are North, South and East and the gender dummy is Female. Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.5138 0.2637 0.1806 52.650 60 Intercept Age Income North South East Female Coefficients 477.481 2.858 0.024 11.158 13.247 33.946 17.080 Standard Error 44.896 0.907 0.023 3.635 2.834 23.332 14.338 1 Stat 10.635 3.153 1.036 3.070 4.674 1.455 1.191 P-value 0.000 0.003 0.305 0.003 0.002 0.152 0.239 The predicted credit score of a 36 year old male in the South with $3000 of income is 653.63 R Square Adjusted R Square Standard Error Observations 0.2637 0.1806 52.650 Intercept Age Income North South East Female Coefficients 477.481 2.858 0.024 11.158 13.247 33.946 17.080 Standard Error 44.896 0.907 0.023 3.635 2.834 23.332 14.338 Star 10.635 3.153 1.036 3.070 4.674 1.455 1.191 P-value 0.000 0.003 0.305 0.003 0.002 0.152 0.239 The predicted credit score of a 36 year old male in the South with $3000 of income is 0653.63 O 682.70 702.66 665.62 Question 9 (3 points)