Let's consider the following regression model. Estimate the model using Minitab and answer the questions using the output. Loanamt-bi+b, * income + e, Write the equations for the following statistics, find or calculate them from the Minitab output, and explain the meanings of the statistics (2 points each) 1) Estimated intercept 2) Estimated slope coefficient 3) SST (Total Sum of Square), SSR (Regression Sum of Square), and SSE (Error Sum of Square) 4)r and r, t test for the correlation coefficient 5) Standard Error of b 6) t test for the coefficient of income (Ho: B1 = 0) 7) F statistics and perform the test for the model 8) Variance of 9) According to the model what are the predicted loan amount if applicants have annual income of $50,000, $100,000, and $200,000 and their confidence intervals? 10) List and explain the assumptions you made for a simple regression model 00 - + O + 2/2 2 View as Text Download WEEK8 HW GSB420 Let's consinder a mortgage application using HMDA (The Home Mortgage Disclosure Act). Here is a sample from 30 mortgage applications (excel file is available in D2L): ID 1 2 3 78 37 119 58 9/ 117 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 loanamt income hprice 109 63 155 185 137 264 121 53 128 125 125 149 153 171 380 188 484 100 125 110 78 158 41 31 116.5 115 54 128 248 280 126 60 157.5 260 192 325 90 145 50 230 125 125 125 145 158 175 130 209 204 260 30 150 114 143 188 253 187 285 84 105 450 265 650 108 49 120 100 53 125 loanamt-Amount of Mortgage Loan Application (in $1000) income - Applicant's Annual Income (in $1000) hprice - House Price to buy (in $1000) Regression Analyis 00 - + O + 1127 View as Text Download Let's consider the following regression model. Estimate the model using Minitab and answer the questions using the output. Loanamt-bi+b, * income + e, Write the equations for the following statistics, find or calculate them from the Minitab output, and explain the meanings of the statistics (2 points each) 1) Estimated intercept 2) Estimated slope coefficient 3) SST (Total Sum of Square), SSR (Regression Sum of Square), and SSE (Error Sum of Square) 4)r and r, t test for the correlation coefficient 5) Standard Error of b 6) t test for the coefficient of income (Ho: B1 = 0) 7) F statistics and perform the test for the model 8) Variance of 9) According to the model what are the predicted loan amount if applicants have annual income of $50,000, $100,000, and $200,000 and their confidence intervals? 10) List and explain the assumptions you made for a simple regression model 00 - + O + 2/2 2 View as Text Download WEEK8 HW GSB420 Let's consinder a mortgage application using HMDA (The Home Mortgage Disclosure Act). Here is a sample from 30 mortgage applications (excel file is available in D2L): ID 1 2 3 78 37 119 58 9/ 117 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 loanamt income hprice 109 63 155 185 137 264 121 53 128 125 125 149 153 171 380 188 484 100 125 110 78 158 41 31 116.5 115 54 128 248 280 126 60 157.5 260 192 325 90 145 50 230 125 125 125 145 158 175 130 209 204 260 30 150 114 143 188 253 187 285 84 105 450 265 650 108 49 120 100 53 125 loanamt-Amount of Mortgage Loan Application (in $1000) income - Applicant's Annual Income (in $1000) hprice - House Price to buy (in $1000) Regression Analyis 00 - + O + 1127 View as Text Download
