Open the Excel spreadsheet "HomeSalesData.xls". This dataset shows actual home sales data from New Orleans, circa 2005. Estimate a regression to answer the following. Each additional BATH in a house is associated with a _____________ dollar increase home price. Round your answer to two decimal places. Price Home_Size Lot_Size Number_Rooms Number_Baths $72,000 600 0.50 3 1.0 $116,300 1050 0.43 5 1.5 $152,000 1800 0.68 7 1.5 $80,500 922 0.30 5 1.0 $141,900 1950 0.75 8 2.5 $124,000 1783 0.22 8 1.5 $117,000 1008 0.50 6 1.0 $165,900 1840 1.16 8 2.0 $153,500 3700 1.10 10 3.0 $126,500 1092 0.26 6 1.0 $122,000 1950 0.50 7 1.5 $140,000 1403 0.50 6 2.0 $223,000 1680 14.37 8 2.0 $99,500 1000 0.49 4 1.0 $211,900 2310 0.46 8 2.5 $121,900 1300 0.78 6 1.0 $169,000 1930 3.00 9 3.0 $156,000 3000 0.50 11 2.5 $123,500 1362 0.40 7 2.0 $136,000 1750 0.50 7 2.0 $194,900 2080 1.00 8 2.5 $128,500 1344 0.94 6 2.0 $302,000 2130 11.91 8 1.5 $142,000 1500 0.41 7 1.0 $146,000 2400 0.40 7 2.5 $180,000 2272 0.41 9 2.5 $126,500 1050 1.00 5 1.0 $139,500 1610 0.45 8 1.5 $124,900 1248 0.22 7 1.0 $133,000 2000 0.50 8 2.0 $110,000 1450 0.30 6 2.0 $118,500 1248 0.25 7 1.0 $194,500 2544 0.28 9 2.5 $269,900 2500 0.92 8 3.0 $169,900 2858 0.79 9 3.0 $190,000 1745 0.58 7 2.5 $203,000 2653 1.80 9 3.0 $144,900 1450 0.30 7 1.0 $94,000 850 0.11 4 1.0 $139,900 1839 2.60 7 1.5 $183,000 2016 0.78 8 2.5 $135,000 1625 0.36 7 1.5 $132,000 2000 0.11 8 2.0 $181,500 2250 0.33 9 2.5 $136,000 1300 0.30 7 1.0 $164,000 1956 0.50 8 2.5 $162,000 2496 0.75 9 2.5 $141,000 1575 0.25 7 1.5 $196,800 1960 1.33 8 2.5 $125,000 1200 0.33 5 1.0 $127,500 1296 0.50 9 1.0 $267,000 1950 18.70 7 2.5 $285,000 2516 8.10 7 2.5 $131,000 1066 0.33 5 1.0 $163,500 2276 1.00 8 2.5 $133,000 1908 0.46 7 2.0 $150,000 1122 3.09 5 2.0 $141,000 3500 1.00 10 2.5 $133,000 1100 0.33 6 1.0 $190,000 2300 5.63 7 2.5 $125,900 1118 0.56 7 1.5 $189,900 2464 0.43 8 2.5 $155,000 2100 0.58 8 1.5 $142,500 1552 0.46 6 1.5 $137,900 1856 0.33 7 1.5 $130,000 1800 0.30 7 1.5 $117,000 1248 0.30 6 1.0 $180,500 2000 0.60 9 2.5 $162,500 1848 0.50 7 2.5 $108,000 1036 0.95 6 1.0 $170,000 2277 0.80 8 3.0 $156,000 2300 0.65 7 3.0 $187,000 2080 1.23 8 2.5 $150,000 1600 1.84 7 2.0 $165,000 2680 0.50 9 3.0 $119,000 1200 0.25 7 1.0 $135,500 1526 0.30 7 1.5 $145,900 1680 0.50 6 1.5 $126,000 1232 0.31 6 2.0 $205,406 2465 1.55 8 2.5 $185,500 2800 1.68 9 1.5 $195,000 2265 0.85 8 2.5 $125,000 1300 0.65 5 1.0 $160,000 1900 1.00 8 2.5 $96,000 864 0.32 4 1.0 $142,000 2000 0.75 9 1.5 $145,000 1800 0.66 8 2.5 $151,500 1900 0.75 7 2.0 $150,000 1564 0.33 6 2.0 $265,000 2400 2.00 7 2.0 $116,000 1100 1.10 6 1.0 $135,000 1800 1.00 8 2.5 $129,000 1200 0.33 6 1.0 $108,500 1540 0.18 7 2.0 $164,900 1980 0.70 8 2.5 $110,000 1289 0.25 6 1.0 $154,000 1800 0.68 7 2.0 $134,000 1502 0.35 7 1.5 $160,000 2025 1.10 7 2.0 $220,000 3000 1.15 10 3.5 $126,500 1500 0.50 7 1.5 $126,500 1600 0.26 8 1.5 $158,000 1500 0.54 5 2.5 $172,000 2100 1.00 8 2.5 $215,000 2100 0.50 8 2.5 $141,900 1632 3.00 6 3.0 $89,900 1660 0.21 7 1.0 $129,900 1070 1.69 5 1.0 $135,000 1400 0.35 6 2.0 $135,000 1800 0.50 7 2.0 $122,500 1100 0.37 7 1.0 $235,000 3150 0.30 11 4.0 $134,500 2000 0.70 8 1.0 $126,500 1700 0.30 8 2.0 $180,000 1800 1.52 8 2.5 $127,500 1850 0.26 9 2.0 $165,000 2320 0.40 8 2.5 $97,000 1300 0.37 5 1.0 $100,000 1338 0.12 6 1.0 $208,000 2288 1.20 8 2.5 $182,000 2400 0.50 8 2.5 $175,000 2400 0.70 8 3.0 $144,900 1900 0.44 6 2.0 $177,000 2010 0.68 8 1.5 $231,750 2981 1.30 10 3.5 $165,000 1725 1.53 8 2.5 $78,000 821 2.30 4 1.0 $179,000 3060 0.75 8 2.0 $85,000 875 0.26 5 1.0 $160,000 1760 0.05 7 2.0 $141,000 2000 0.65 7 1.0 $185,000 2600 0.75 8 2.0 $113,500 1624 1.80 7 1.5 $190,000 2473 1.25 9 2.5 $107,000 1100 0.17 5 1.0 $217,000 3100 0.54 10 3.5 $194,500 2300 0.91 8 2.5 $152,000 1450 0.30 6 1.5 $210,000 2100 0.50 8 2.5 $140,000 1650 0.50 8 2.5 $120,500 1600 0.40 6 2.0 $179,900 2790 0.75 13 2.5 $152,500 1786 0.30 8 2.0 $159,000 1728 0.50 8 1.5 $168,500 1900 1.06 7 2.5 $98,000 1165 0.12 6 1.0 $117,500 1300 0.29 6 1.0 $115,000 1080 0.31 5 1.0 $275,000 2820 1.00 9 2.5 $190,000 2100 1.30 8 1.5
Open the Excel spreadsheet "HomeSalesData.xls". This dataset shows actual home sales data from New Orleans, circa 2005. Estimate a regression to answer the following. Each additional BATH in a house is associated with a _____________ dollar increase home price. Round your answer to two decimal places. Price Home_Size Lot_Size Number_Rooms Number_Baths $72,000 600 0.50 3 1.0 $116,300 1050 0.43 5 1.5 $152,000 1800 0.68 7 1.5 $80,500 922 0.30 5 1.0 $141,900 1950 0.75 8 2.5 $124,000 1783 0.22 8 1.5 $117,000 1008 0.50 6 1.0 $165,900 1840 1.16 8 2.0 $153,500 3700 1.10 10 3.0 $126,500 1092 0.26 6 1.0 $122,000 1950 0.50 7 1.5 $140,000 1403 0.50 6 2.0 $223,000 1680 14.37 8 2.0 $99,500 1000 0.49 4 1.0 $211,900 2310 0.46 8 2.5 $121,900 1300 0.78 6 1.0 $169,000 1930 3.00 9 3.0 $156,000 3000 0.50 11 2.5 $123,500 1362 0.40 7 2.0 $136,000 1750 0.50 7 2.0 $194,900 2080 1.00 8 2.5 $128,500 1344 0.94 6 2.0 $302,000 2130 11.91 8 1.5 $142,000 1500 0.41 7 1.0 $146,000 2400 0.40 7 2.5 $180,000 2272 0.41 9 2.5 $126,500 1050 1.00 5 1.0 $139,500 1610 0.45 8 1.5 $124,900 1248 0.22 7 1.0 $133,000 2000 0.50 8 2.0 $110,000 1450 0.30 6 2.0 $118,500 1248 0.25 7 1.0 $194,500 2544 0.28 9 2.5 $269,900 2500 0.92 8 3.0 $169,900 2858 0.79 9 3.0 $190,000 1745 0.58 7 2.5 $203,000 2653 1.80 9 3.0 $144,900 1450 0.30 7 1.0 $94,000 850 0.11 4 1.0 $139,900 1839 2.60 7 1.5 $183,000 2016 0.78 8 2.5 $135,000 1625 0.36 7 1.5 $132,000 2000 0.11 8 2.0 $181,500 2250 0.33 9 2.5 $136,000 1300 0.30 7 1.0 $164,000 1956 0.50 8 2.5 $162,000 2496 0.75 9 2.5 $141,000 1575 0.25 7 1.5 $196,800 1960 1.33 8 2.5 $125,000 1200 0.33 5 1.0 $127,500 1296 0.50 9 1.0 $267,000 1950 18.70 7 2.5 $285,000 2516 8.10 7 2.5 $131,000 1066 0.33 5 1.0 $163,500 2276 1.00 8 2.5 $133,000 1908 0.46 7 2.0 $150,000 1122 3.09 5 2.0 $141,000 3500 1.00 10 2.5 $133,000 1100 0.33 6 1.0 $190,000 2300 5.63 7 2.5 $125,900 1118 0.56 7 1.5 $189,900 2464 0.43 8 2.5 $155,000 2100 0.58 8 1.5 $142,500 1552 0.46 6 1.5 $137,900 1856 0.33 7 1.5 $130,000 1800 0.30 7 1.5 $117,000 1248 0.30 6 1.0 $180,500 2000 0.60 9 2.5 $162,500 1848 0.50 7 2.5 $108,000 1036 0.95 6 1.0 $170,000 2277 0.80 8 3.0 $156,000 2300 0.65 7 3.0 $187,000 2080 1.23 8 2.5 $150,000 1600 1.84 7 2.0 $165,000 2680 0.50 9 3.0 $119,000 1200 0.25 7 1.0 $135,500 1526 0.30 7 1.5 $145,900 1680 0.50 6 1.5 $126,000 1232 0.31 6 2.0 $205,406 2465 1.55 8 2.5 $185,500 2800 1.68 9 1.5 $195,000 2265 0.85 8 2.5 $125,000 1300 0.65 5 1.0 $160,000 1900 1.00 8 2.5 $96,000 864 0.32 4 1.0 $142,000 2000 0.75 9 1.5 $145,000 1800 0.66 8 2.5 $151,500 1900 0.75 7 2.0 $150,000 1564 0.33 6 2.0 $265,000 2400 2.00 7 2.0 $116,000 1100 1.10 6 1.0 $135,000 1800 1.00 8 2.5 $129,000 1200 0.33 6 1.0 $108,500 1540 0.18 7 2.0 $164,900 1980 0.70 8 2.5 $110,000 1289 0.25 6 1.0 $154,000 1800 0.68 7 2.0 $134,000 1502 0.35 7 1.5 $160,000 2025 1.10 7 2.0 $220,000 3000 1.15 10 3.5 $126,500 1500 0.50 7 1.5 $126,500 1600 0.26 8 1.5 $158,000 1500 0.54 5 2.5 $172,000 2100 1.00 8 2.5 $215,000 2100 0.50 8 2.5 $141,900 1632 3.00 6 3.0 $89,900 1660 0.21 7 1.0 $129,900 1070 1.69 5 1.0 $135,000 1400 0.35 6 2.0 $135,000 1800 0.50 7 2.0 $122,500 1100 0.37 7 1.0 $235,000 3150 0.30 11 4.0 $134,500 2000 0.70 8 1.0 $126,500 1700 0.30 8 2.0 $180,000 1800 1.52 8 2.5 $127,500 1850 0.26 9 2.0 $165,000 2320 0.40 8 2.5 $97,000 1300 0.37 5 1.0 $100,000 1338 0.12 6 1.0 $208,000 2288 1.20 8 2.5 $182,000 2400 0.50 8 2.5 $175,000 2400 0.70 8 3.0 $144,900 1900 0.44 6 2.0 $177,000 2010 0.68 8 1.5 $231,750 2981 1.30 10 3.5 $165,000 1725 1.53 8 2.5 $78,000 821 2.30 4 1.0 $179,000 3060 0.75 8 2.0 $85,000 875 0.26 5 1.0 $160,000 1760 0.05 7 2.0 $141,000 2000 0.65 7 1.0 $185,000 2600 0.75 8 2.0 $113,500 1624 1.80 7 1.5 $190,000 2473 1.25 9 2.5 $107,000 1100 0.17 5 1.0 $217,000 3100 0.54 10 3.5 $194,500 2300 0.91 8 2.5 $152,000 1450 0.30 6 1.5 $210,000 2100 0.50 8 2.5 $140,000 1650 0.50 8 2.5 $120,500 1600 0.40 6 2.0 $179,900 2790 0.75 13 2.5 $152,500 1786 0.30 8 2.0 $159,000 1728 0.50 8 1.5 $168,500 1900 1.06 7 2.5 $98,000 1165 0.12 6 1.0 $117,500 1300 0.29 6 1.0 $115,000 1080 0.31 5 1.0 $275,000 2820 1.00 9 2.5 $190,000 2100 1.30 8 1.5
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Open the Excel spreadsheet "HomeSalesData.xls". This dataset shows actual home sales data from New Orleans, circa 2005. Estimate a regression to answer the following.
Each additional BATH in a house is associated with a _____________ dollar increase home price. Round your answer to two decimal places.
| Price | Home_Size | Lot_Size | Number_Rooms | Number_Baths |
| $72,000 | 600 | 0.50 | 3 | 1.0 |
| $116,300 | 1050 | 0.43 | 5 | 1.5 |
| $152,000 | 1800 | 0.68 | 7 | 1.5 |
| $80,500 | 922 | 0.30 | 5 | 1.0 |
| $141,900 | 1950 | 0.75 | 8 | 2.5 |
| $124,000 | 1783 | 0.22 | 8 | 1.5 |
| $117,000 | 1008 | 0.50 | 6 | 1.0 |
| $165,900 | 1840 | 1.16 | 8 | 2.0 |
| $153,500 | 3700 | 1.10 | 10 | 3.0 |
| $126,500 | 1092 | 0.26 | 6 | 1.0 |
| $122,000 | 1950 | 0.50 | 7 | 1.5 |
| $140,000 | 1403 | 0.50 | 6 | 2.0 |
| $223,000 | 1680 | 14.37 | 8 | 2.0 |
| $99,500 | 1000 | 0.49 | 4 | 1.0 |
| $211,900 | 2310 | 0.46 | 8 | 2.5 |
| $121,900 | 1300 | 0.78 | 6 | 1.0 |
| $169,000 | 1930 | 3.00 | 9 | 3.0 |
| $156,000 | 3000 | 0.50 | 11 | 2.5 |
| $123,500 | 1362 | 0.40 | 7 | 2.0 |
| $136,000 | 1750 | 0.50 | 7 | 2.0 |
| $194,900 | 2080 | 1.00 | 8 | 2.5 |
| $128,500 | 1344 | 0.94 | 6 | 2.0 |
| $302,000 | 2130 | 11.91 | 8 | 1.5 |
| $142,000 | 1500 | 0.41 | 7 | 1.0 |
| $146,000 | 2400 | 0.40 | 7 | 2.5 |
| $180,000 | 2272 | 0.41 | 9 | 2.5 |
| $126,500 | 1050 | 1.00 | 5 | 1.0 |
| $139,500 | 1610 | 0.45 | 8 | 1.5 |
| $124,900 | 1248 | 0.22 | 7 | 1.0 |
| $133,000 | 2000 | 0.50 | 8 | 2.0 |
| $110,000 | 1450 | 0.30 | 6 | 2.0 |
| $118,500 | 1248 | 0.25 | 7 | 1.0 |
| $194,500 | 2544 | 0.28 | 9 | 2.5 |
| $269,900 | 2500 | 0.92 | 8 | 3.0 |
| $169,900 | 2858 | 0.79 | 9 | 3.0 |
| $190,000 | 1745 | 0.58 | 7 | 2.5 |
| $203,000 | 2653 | 1.80 | 9 | 3.0 |
| $144,900 | 1450 | 0.30 | 7 | 1.0 |
| $94,000 | 850 | 0.11 | 4 | 1.0 |
| $139,900 | 1839 | 2.60 | 7 | 1.5 |
| $183,000 | 2016 | 0.78 | 8 | 2.5 |
| $135,000 | 1625 | 0.36 | 7 | 1.5 |
| $132,000 | 2000 | 0.11 | 8 | 2.0 |
| $181,500 | 2250 | 0.33 | 9 | 2.5 |
| $136,000 | 1300 | 0.30 | 7 | 1.0 |
| $164,000 | 1956 | 0.50 | 8 | 2.5 |
| $162,000 | 2496 | 0.75 | 9 | 2.5 |
| $141,000 | 1575 | 0.25 | 7 | 1.5 |
| $196,800 | 1960 | 1.33 | 8 | 2.5 |
| $125,000 | 1200 | 0.33 | 5 | 1.0 |
| $127,500 | 1296 | 0.50 | 9 | 1.0 |
| $267,000 | 1950 | 18.70 | 7 | 2.5 |
| $285,000 | 2516 | 8.10 | 7 | 2.5 |
| $131,000 | 1066 | 0.33 | 5 | 1.0 |
| $163,500 | 2276 | 1.00 | 8 | 2.5 |
| $133,000 | 1908 | 0.46 | 7 | 2.0 |
| $150,000 | 1122 | 3.09 | 5 | 2.0 |
| $141,000 | 3500 | 1.00 | 10 | 2.5 |
| $133,000 | 1100 | 0.33 | 6 | 1.0 |
| $190,000 | 2300 | 5.63 | 7 | 2.5 |
| $125,900 | 1118 | 0.56 | 7 | 1.5 |
| $189,900 | 2464 | 0.43 | 8 | 2.5 |
| $155,000 | 2100 | 0.58 | 8 | 1.5 |
| $142,500 | 1552 | 0.46 | 6 | 1.5 |
| $137,900 | 1856 | 0.33 | 7 | 1.5 |
| $130,000 | 1800 | 0.30 | 7 | 1.5 |
| $117,000 | 1248 | 0.30 | 6 | 1.0 |
| $180,500 | 2000 | 0.60 | 9 | 2.5 |
| $162,500 | 1848 | 0.50 | 7 | 2.5 |
| $108,000 | 1036 | 0.95 | 6 | 1.0 |
| $170,000 | 2277 | 0.80 | 8 | 3.0 |
| $156,000 | 2300 | 0.65 | 7 | 3.0 |
| $187,000 | 2080 | 1.23 | 8 | 2.5 |
| $150,000 | 1600 | 1.84 | 7 | 2.0 |
| $165,000 | 2680 | 0.50 | 9 | 3.0 |
| $119,000 | 1200 | 0.25 | 7 | 1.0 |
| $135,500 | 1526 | 0.30 | 7 | 1.5 |
| $145,900 | 1680 | 0.50 | 6 | 1.5 |
| $126,000 | 1232 | 0.31 | 6 | 2.0 |
| $205,406 | 2465 | 1.55 | 8 | 2.5 |
| $185,500 | 2800 | 1.68 | 9 | 1.5 |
| $195,000 | 2265 | 0.85 | 8 | 2.5 |
| $125,000 | 1300 | 0.65 | 5 | 1.0 |
| $160,000 | 1900 | 1.00 | 8 | 2.5 |
| $96,000 | 864 | 0.32 | 4 | 1.0 |
| $142,000 | 2000 | 0.75 | 9 | 1.5 |
| $145,000 | 1800 | 0.66 | 8 | 2.5 |
| $151,500 | 1900 | 0.75 | 7 | 2.0 |
| $150,000 | 1564 | 0.33 | 6 | 2.0 |
| $265,000 | 2400 | 2.00 | 7 | 2.0 |
| $116,000 | 1100 | 1.10 | 6 | 1.0 |
| $135,000 | 1800 | 1.00 | 8 | 2.5 |
| $129,000 | 1200 | 0.33 | 6 | 1.0 |
| $108,500 | 1540 | 0.18 | 7 | 2.0 |
| $164,900 | 1980 | 0.70 | 8 | 2.5 |
| $110,000 | 1289 | 0.25 | 6 | 1.0 |
| $154,000 | 1800 | 0.68 | 7 | 2.0 |
| $134,000 | 1502 | 0.35 | 7 | 1.5 |
| $160,000 | 2025 | 1.10 | 7 | 2.0 |
| $220,000 | 3000 | 1.15 | 10 | 3.5 |
| $126,500 | 1500 | 0.50 | 7 | 1.5 |
| $126,500 | 1600 | 0.26 | 8 | 1.5 |
| $158,000 | 1500 | 0.54 | 5 | 2.5 |
| $172,000 | 2100 | 1.00 | 8 | 2.5 |
| $215,000 | 2100 | 0.50 | 8 | 2.5 |
| $141,900 | 1632 | 3.00 | 6 | 3.0 |
| $89,900 | 1660 | 0.21 | 7 | 1.0 |
| $129,900 | 1070 | 1.69 | 5 | 1.0 |
| $135,000 | 1400 | 0.35 | 6 | 2.0 |
| $135,000 | 1800 | 0.50 | 7 | 2.0 |
| $122,500 | 1100 | 0.37 | 7 | 1.0 |
| $235,000 | 3150 | 0.30 | 11 | 4.0 |
| $134,500 | 2000 | 0.70 | 8 | 1.0 |
| $126,500 | 1700 | 0.30 | 8 | 2.0 |
| $180,000 | 1800 | 1.52 | 8 | 2.5 |
| $127,500 | 1850 | 0.26 | 9 | 2.0 |
| $165,000 | 2320 | 0.40 | 8 | 2.5 |
| $97,000 | 1300 | 0.37 | 5 | 1.0 |
| $100,000 | 1338 | 0.12 | 6 | 1.0 |
| $208,000 | 2288 | 1.20 | 8 | 2.5 |
| $182,000 | 2400 | 0.50 | 8 | 2.5 |
| $175,000 | 2400 | 0.70 | 8 | 3.0 |
| $144,900 | 1900 | 0.44 | 6 | 2.0 |
| $177,000 | 2010 | 0.68 | 8 | 1.5 |
| $231,750 | 2981 | 1.30 | 10 | 3.5 |
| $165,000 | 1725 | 1.53 | 8 | 2.5 |
| $78,000 | 821 | 2.30 | 4 | 1.0 |
| $179,000 | 3060 | 0.75 | 8 | 2.0 |
| $85,000 | 875 | 0.26 | 5 | 1.0 |
| $160,000 | 1760 | 0.05 | 7 | 2.0 |
| $141,000 | 2000 | 0.65 | 7 | 1.0 |
| $185,000 | 2600 | 0.75 | 8 | 2.0 |
| $113,500 | 1624 | 1.80 | 7 | 1.5 |
| $190,000 | 2473 | 1.25 | 9 | 2.5 |
| $107,000 | 1100 | 0.17 | 5 | 1.0 |
| $217,000 | 3100 | 0.54 | 10 | 3.5 |
| $194,500 | 2300 | 0.91 | 8 | 2.5 |
| $152,000 | 1450 | 0.30 | 6 | 1.5 |
| $210,000 | 2100 | 0.50 | 8 | 2.5 |
| $140,000 | 1650 | 0.50 | 8 | 2.5 |
| $120,500 | 1600 | 0.40 | 6 | 2.0 |
| $179,900 | 2790 | 0.75 | 13 | 2.5 |
| $152,500 | 1786 | 0.30 | 8 | 2.0 |
| $159,000 | 1728 | 0.50 | 8 | 1.5 |
| $168,500 | 1900 | 1.06 | 7 | 2.5 |
| $98,000 | 1165 | 0.12 | 6 | 1.0 |
| $117,500 | 1300 | 0.29 | 6 | 1.0 |
| $115,000 | 1080 | 0.31 | 5 | 1.0 |
| $275,000 | 2820 | 1.00 | 9 | 2.5 |
| $190,000 | 2100 | 1.30 | 8 | 1.5 |
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