york Question 7, 2.2.7 HW Score: 79.09%, 79.09 of 100 points Part 3 of 5 Points: 1.6 of 8 Save The database summarizes financial information for 32 companies and their perceived risk of default. Convert these data into an Excel table. Use table-based calculations to find the average debt and average equity for companies with a risk of default, and also for those without a risk of default. Does there appear to be a difference between companies with and without a risk of default? Click the icon to view the financial information for the 32 companies. Convert these data into an Excel table. Use table-based calculations to find the average debt for companies with a risk of default. The average debt for companies with a risk of default is $ 11796597 . (Round to the nearest whole number as needed.) Use table-based calculations to find the average debt for companies without a risk of default. The average debt for companies without a risk of default is $ 5,975,895. (Round to the nearest whole number as needed.) Use table-based calculations to find the average equity for companies with a risk of default. The average equity for companies with a risk of default is $ (Round to the nearest whole number as needed.).41 V 2.} Company A B C D E F 1 I Companvl Cate a Credit Score Debt E ui Default Assessment 2 1 Service 604 10318588 3820882 Yes 3 2 Manufacturing 214 4019529 2216629 No 4 3 Manufacturing 232 121402 1282238 No 5 4 Manufacturing 292 8084984 11918008 No 6 5 Service 623 3120222\" 255648 Yes 2 6 Manufacturing 202 13199925 4095523 Yes 8 2 Service 264 4116956 6842610 '10 9 8 Manufacturing 690 2121992 5938446 '10 10 9 Service 802 2969203 11550605 '10 11 10 Service 610 14389222 3686534 Yes 12 11 Manufacturing 590 8003522 19928215 '10 13 12 Manufacturing 824 583316 31212038 '10 14 13 Service 262 2252811 4519299 '10 15 14 Manufacturing 601 1226398 305258 Yes 16 15 Manufacturing 655 39129388 14992345 Yes 12 16 Manufacturing 292 4634852 4612049 '10 18 12 Manufacturing 221 3922182 14233030 '10 19 18 Manufacturing 250 12692223 11439891 '10 20 19 Manufacturing 262 5159636 18835016 '10 21 20 Service 598 2515454 538035 Yes 22 21 Manufacturing 242 2025389 4262423 '10 23 22 Manufacturing 821 3668641 14139966 '10 24 23 Service 652 3815520 5221226 Yes 25 24 Manufacturing 298 3102214 3263235 '10 26 25 Manufacturing 695 9822320 5642938 '10 22 26 Service 819 10026016 9212560 '10 28 22 Manufacturing 621 23680348 6665122 Yes 29 28 Manufacturing 221 9803239 6246115 '10 30 29 Service 832 11544319 13919641 '10 31 30 Service 259 821358 1656859 '10 32 31 Manufacturing 613 5920006 801662 Yes 33 32 Manufacturing 205 6262921 5822809 '10 (.0 41-. Part 2 of 2 Points: 4.92 of 8 Sav Use INDEX and MATCH functions to fill in a table that extracts the amounts shipped between each pair of cities in the accompanying data, which shows the From To Amount Shipped solution to an optimization model that finds the minimum cost and amounts shipped from two plants to four distribution centers. Your table should be set up Marietta Cleveland as follows, and the formulas for the Amount Shipped column should reference the names in the From and To columns. Marietta Baltimore Marietta Chicago Marietta Phoenix Minneapolis Cleveland Minneapolis Baltimore Minneapolis Chicago Minneapolis Phoenix Click the icon to view the data and model. . . . Let cell range B11:E12 be named "Model," let cell range A11:A12 be named "Plant," and let cell range B10:E10 be named "Center." Select the appropriate INDEX and MATCH functions to complete the spreadsheet below. H 1 From To Amount Shipped 2 Marietta Cleveland =INDEX(Model, MATCH(H2, Plant, 0), MATCH(12, Center,0)) 3 |Marietta Baltimore =INDEX(Model, MATCH(H3, Plant, 0), MATCH(13, Center, 0)) 4 Marietta Chicago =INDEX(Model, MATCH(H4, Plant,0), MATCH(14, Center,0)) 5 |Marietta Phoenix =INDEX(Model, MATCH(H5, Plant,0), MATCH(15, Center,0)) 6 Minneapolis Cleveland =INDEX(Model, MATCH(H6,Plant, 0), MATCH(16, Center,0)) 7 Minneapolis |Baltimore =INDEX(Model,MATCH(H7, Plant,0), MATCH(17, Center,0)) 8 Minneapolis Chicago =INDEX(Model, MATCH(H8,Plant, 0), MATCH(18, Center,0)) Minneapolis Phoenix =INDEX(Model, MATCH(H9,Plant,0), MATCH(19, Center,0)) Replace the functions with the amounts shipped between each pair of cities.Replace the functions with the amounts shipped between each pair of cities. From To Amount Shipped Marietta Cleveland 0 Marietta Baltimore Marietta Chicago 0 Marietta Phoenix Minneapolis Cleveland Minneapolis Baltimore O Minneapolis Chicago Minneapolis PhoenixGeneral Appliance Corporation A B C D E F 1 Data 2 Distribution Center 3 PlantCleveland Baltimore Chicago Phoenix Capacity 4 Marietta $13.24 $14.66 $11.63 $17.84 1050 5 Minneapolis $9.71 $16.38 $8.08 $17.95 900 6 Demand 200 250 500 1000 7 8 Model Distribution Center 10 Plant Cleveland Baltimore Chicago Phoenix Total Shipped 11 Marietta 0 250 800 1050 12 Minneapolis 200 0 500 200 900 13 Demand 200 250 500 1000 14 15 Cost 16 Total $27,509