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 square foot increase in home size is associated with a _____________ dollar increase home price. Round your answer to two decimal places. Data on Potentially Related Variables for Randomly Selected Homes PriceHome_SizeLot_SizeNumber_RoomsNumber_Baths$72,0006000.5031.0$116,30010500.4351.5$152,00018000.6871.5$80,5009220.3051.0$141,90019500.7582.5$124,00017830.2281.5$117,00010080.5061.0$165,90018401.1682.0$153,50037001.10103.0$126,50010920.2661.0$122,00019500.5071.5$140,00014030.5062.0$223,000168014.3782.0$99,50010000.4941.0$211,90023100.4682.5$121,90013000.7861.0$169,00019303.0093.0$156,00030000.50112.5$123,50013620.4072.0$136,00017500.5072.0$194,90020801.0082.5$128,50013440.9462.0$302,000213011.9181.5$142,00015000.4171.0$146,00024000.4072.5$180,00022720.4192.5$126,50010501.0051.0$139,50016100.4581.5$124,90012480.2271.0$133,00020000.5082.0$110,00014500.3062.0$118,50012480.2571.0$194,50025440.2892.5$269,90025000.9283.0$169,90028580.7993.0$190,00017450.5872.5$203,00026531.8093.0$144,90014500.3071.0$94,0008500.1141.0$139,90018392.6071.5$183,00020160.7882.5$135,00016250.3671.5$132,00020000.1182.0$181,50022500.3392.5$136,00013000.3071.0$164,00019560.5082.5$162,00024960.7592.5$141,00015750.2571.5$196,80019601.3382.5$125,00012000.3351.0$127,50012960.5091.0$267,000195018.7072.5$285,00025168.1072.5$131,00010660.3351.0$163,50022761.0082.5$133,00019080.4672.0$150,00011223.0952.0$141,00035001.00102.5$133,00011000.3361.0$190,00023005.6372.5$125,90011180.5671.5$189,90024640.4382.5$155,00021000.5881.5$142,50015520.4661.5$137,90018560.3371.5$130,00018000.3071.5$117,00012480.3061.0$180,50020000.6092.5$162,50018480.5072.5$108,00010360.9561.0$170,00022770.8083.0$156,00023000.6573.0$187,00020801.2382.5$150,00016001.8472.0$165,00026800.5093.0$119,00012000.2571.0$135,50015260.3071.5$145,90016800.5061.5$126,00012320.3162.0$205,40624651.5582.5$185,50028001.6891.5$195,00022650.8582.5$125,00013000.6551.0$160,00019001.0082.5$96,0008640.3241.0$142,00020000.7591.5$145,00018000.6682.5$151,50019000.7572.0$150,00015640.3362.0$265,00024002.0072.0$116,00011001.1061.0$135,00018001.0082.5$129,00012000.3361.0$108,50015400.1872.0$164,90019800.7082.5$110,00012890.2561.0$154,00018000.6872.0$134,00015020.3571.5$160,00020251.1072.0$220,00030001.15103.5$126,50015000.5071.5$126,50016000.2681.5$158,00015000.5452.5$172,00021001.0082.5$215,00021000.5082.5$141,90016323.0063.0$89,90016600.2171.0$129,90010701.6951.0$135,00014000.3562.0$135,00018000.5072.0$122,50011000.3771.0$235,00031500.30114.0$134,50020000.7081.0$126,50017000.3082.0$180,00018001.5282.5$127,50018500.2692.0$165,00023200.4082.5$97,00013000.3751.0$100,00013380.1261.0$208,00022881.2082.5$182,00024000.5082.5$175,00024000.7083.0$144,90019000.4462.0$177,00020100.6881.5$231,75029811.30103.5$165,00017251.5382.5$78,0008212.3041.0$179,00030600.7582.0$85,0008750.2651.0$160,00017600.0572.0$141,00020000.6571.0$185,00026000.7582.0$113,50016241.8071.5$190,00024731.2592.5$107,00011000.1751.0$217,00031000.54103.5$194,50023000.9182.5$152,00014500.3061.5$210,00021000.5082.5$140,00016500.5082.5$120,50016000.4062.0$179,90027900.75132.5$152,50017860.3082.0$159,00017280.5081.5$168,50019001.0672.5$98,00011650.1261.0$117,50013000.2961.0$115,00010800.3151.0$275,00028201.0092.5$190,00021001.3081.5

From the given information, the variables in the data set includes: Price, Home size , Lot size,…

Answered: Open the Excel spreadsheet…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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 square foot increase in home size is associated with a _____________ dollar increase home price. Round your answer to two decimal places.

Data on Potentially Related Variables for Randomly Selected Homes

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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