Extract the records for business loans in the Excel file credit risk data and code the non-numerical data. Apply discriminate analysis to classify the credit risk for the business loans in the records to classify worksheet.

I believe part of the question is already completed but im unsure the steps to finish the rest

B D E F G H K M 2 2 3 Gender Job 0 Credit Risk 0 4 1 5 1 1 1 1 6 7 1 0 0 0 0 0 0 8 9 10 11 12 1 1 1 1 1 Housing Years 0 1 0 0 1 0 3 1 4 0 4 4 0 4 0 2 0 4 1 4 0 2 0 2 0 4 0 3 0 2. 2 0 1 0 1 1 4 0 2 1 4 0 2 0 3 1 0 1 1 1 1 1 0 1 1 1 1 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 1 Business 28 0 1 0 0 1 1 1 Loan Purpose Checking Business $0 Business $322 Business $141 Business Dolce $16,647 Business Dance $758 Business $0 Business $674 Business $15,328 Business $12,760 Business $0 Buscinoce co Business $0 Business $0 $ Business $172 Business $663 $0 Business $986 SUBS Business $859 Business $0 Business $177 Business $929 Business $0 Business $O Business $0 Business $0 0 Business $870 Business $9,783 Business $522 Business $0 Business $509 Business $339 $ Business 0 $0 Business $0 Business Business $8,948 Business $498 Business $0 os Business $778 Business $0 Business $0 Business $0 Business $257 Business $898 Business $670 Business $444 1 Savings Months Customer $533 14 $578 10 $245 22 $895 16 $2,665 13 $322 28 $2,886 49 en $0 25 $4,873 13 $104 $ 25 $265 43 13 $406 6 $0 25 $0 19 $922 2 19 $578 $3,305 25 $3,285 7 $0 49 $124 9 $4,973 25 $989 49 $150 49 $724 25 $917 28 $885 13 $194 25 $565 19 $241 25 $2,790 22 $750 37 $5,180 22 $1,435 49 $110 31 $598 37 ws $800 49 $861 49 $500 25 $11,481 25 $859 19 $460 49 $177 31 $921 28 Months Employed 2 14 33 34 31 28 32 9 73 23 10 35 36 57 29 1 26 21 9 9 1 17 0 46 8 6 6 3 79 14 14 55 2 4 14 14 90 14 2 21 1 18 23 75 105 21 51 1 1 2 0 1 1 0 2 1 0 0 0 1 Marital Status Age 0 0 27 1 26 0 0 26 0 25 0 38 . 0 25 0 29 2 0 31 0 ES 56 4 1 20 2 26 0 0 73 0 33 0 41 0 33 2 31 0 35 0 33 0 37 1 25 0 26 0 32 20 2 36 0 30 0 35 2 2 25 2 30 1 27 0 35 en 2 60 2 27 0 40 2 37 SI 0 0 65 29 2 - 2 23 0 22 0 26 0 53 0 35 2 2 58 2 38 2 25 2 41 13 14 15 15 16 17 18 18 19 20 21 22 23 24 25 26 27 20 28 29 30 31 32 33 34 25 35 36 37 S 38 39 40 41 1 1 2 0 1 1 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 4 2 2 2 1 1 4 2 4 2 1 2 2 2 4 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 $2,715 1 1 1 1 1 1 " 1 1 0 0 1 1 2 2 1 1 1 0 0 1 1 0 1 1 2 2 1 1 1 2 1 1 1 1 0 2 1 1 1 4 0 1 1 1 1 0 0 0 0 42 43 2 2 3 2 3 4 4 4 1 1 0 o 0 0 1 1 1 . 1 1 1 1 1 1 44 22 1 0 1 1 $4,014 45 . 46 47 48 49 50 51 52 53 54 Female = 0 Male = 1 Single = 0 Married = 1 Divorced = 2 Own = 0 Rent = 1 Unskilled = 0 Skilled = 1 Management = 2 Low = 0 High = 1 55 M N N O a Q R U u w x AA Months Employed Gender Job Credit Risk Loan Purpose Business Business Checking $500 $790 Savings Months Custo S800 15 $3,000 8 20 24 Marital Status Age 1 0 0 1 1 1 Housing Years 1 1 26 39 7 0 2 2 3 3 4 5 6 7 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 SS 10. Extract the records for business loans in the Excel file Credit Risk Data and code the non- numerical data. Apply discriminant analysis to classify the credit risk for the business loans in the Records to Classify worksheet. B D E F G H K M 2 2 3 Gender Job 0 Credit Risk 0 4 1 5 1 1 1 1 6 7 1 0 0 0 0 0 0 8 9 10 11 12 1 1 1 1 1 Housing Years 0 1 0 0 1 0 3 1 4 0 4 4 0 4 0 2 0 4 1 4 0 2 0 2 0 4 0 3 0 2. 2 0 1 0 1 1 4 0 2 1 4 0 2 0 3 1 0 1 1 1 1 1 0 1 1 1 1 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 1 Business 28 0 1 0 0 1 1 1 Loan Purpose Checking Business $0 Business $322 Business $141 Business Dolce $16,647 Business Dance $758 Business $0 Business $674 Business $15,328 Business $12,760 Business $0 Buscinoce co Business $0 Business $0 $ Business $172 Business $663 $0 Business $986 SUBS Business $859 Business $0 Business $177 Business $929 Business $0 Business $O Business $0 Business $0 0 Business $870 Business $9,783 Business $522 Business $0 Business $509 Business $339 $ Business 0 $0 Business $0 Business Business $8,948 Business $498 Business $0 os Business $778 Business $0 Business $0 Business $0 Business $257 Business $898 Business $670 Business $444 1 Savings Months Customer $533 14 $578 10 $245 22 $895 16 $2,665 13 $322 28 $2,886 49 en $0 25 $4,873 13 $104 $ 25 $265 43 13 $406 6 $0 25 $0 19 $922 2 19 $578 $3,305 25 $3,285 7 $0 49 $124 9 $4,973 25 $989 49 $150 49 $724 25 $917 28 $885 13 $194 25 $565 19 $241 25 $2,790 22 $750 37 $5,180 22 $1,435 49 $110 31 $598 37 ws $800 49 $861 49 $500 25 $11,481 25 $859 19 $460 49 $177 31 $921 28 Months Employed 2 14 33 34 31 28 32 9 73 23 10 35 36 57 29 1 26 21 9 9 1 17 0 46 8 6 6 3 79 14 14 55 2 4 14 14 90 14 2 21 1 18 23 75 105 21 51 1 1 2 0 1 1 0 2 1 0 0 0 1 Marital Status Age 0 0 27 1 26 0 0 26 0 25 0 38 . 0 25 0 29 2 0 31 0 ES 56 4 1 20 2 26 0 0 73 0 33 0 41 0 33 2 31 0 35 0 33 0 37 1 25 0 26 0 32 20 2 36 0 30 0 35 2 2 25 2 30 1 27 0 35 en 2 60 2 27 0 40 2 37 SI 0 0 65 29 2 - 2 23 0 22 0 26 0 53 0 35 2 2 58 2 38 2 25 2 41 13 14 15 15 16 17 18 18 19 20 21 22 23 24 25 26 27 20 28 29 30 31 32 33 34 25 35 36 37 S 38 39 40 41 1 1 2 0 1 1 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 4 2 2 2 1 1 4 2 4 2 1 2 2 2 4 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 $2,715 1 1 1 1 1 1 " 1 1 0 0 1 1 2 2 1 1 1 0 0 1 1 0 1 1 2 2 1 1 1 2 1 1 1 1 0 2 1 1 1 4 0 1 1 1 1 0 0 0 0 42 43 2 2 3 2 3 4 4 4 1 1 0 o 0 0 1 1 1 . 1 1 1 1 1 1 44 22 1 0 1 1 $4,014 45 . 46 47 48 49 50 51 52 53 54 Female = 0 Male = 1 Single = 0 Married = 1 Divorced = 2 Own = 0 Rent = 1 Unskilled = 0 Skilled = 1 Management = 2 Low = 0 High = 1 55 M N N O a Q R U u w x AA Months Employed Gender Job Credit Risk Loan Purpose Business Business Checking $500 $790 Savings Months Custo S800 15 $3,000 8 20 24 Marital Status Age 1 0 0 1 1 1 Housing Years 1 1 26 39 7 0 2 2 3 3 4 5 6 7 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 SS 10. Extract the records for business loans in the Excel file Credit Risk Data and code the non- numerical data. Apply discriminant analysis to classify the credit risk for the business loans in the Records to Classify worksheet