A realty company wants to create a linear model that will estimate the selling price of homes as a function of family. There is particular concern for obtaining the most efficient estimate of the relationship between income and house price. The company has collected data on their sales experience over the past years, and the data are contained in the attached table. Complete parts a though d below. Click the icon to view the data. Click the icon to view the upper critical values of the chi-square distribution. a. Estimate the regression of house price on family income. House Price = + 2.35 (Family Income) (Round to two decimal places as needed.)

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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A realty company wants to create a linear model that will estimate the selling price of homes as a function of family. There is
particular concern for obtaining the most efficient estimate of the relationship between income and house price. The company has
collected data on their sales experience over the past years, and the data are contained in the attached table. Complete parts a
though d below.
Click the icon to view the data.
Click the icon to view the upper critical values of the chi-square distribution.
a. Estimate the regression of house price on family income.
House Price = +2.35 (Family Income)
(Round to two decimal places as needed.)
Transcribed Image Text:A realty company wants to create a linear model that will estimate the selling price of homes as a function of family. There is particular concern for obtaining the most efficient estimate of the relationship between income and house price. The company has collected data on their sales experience over the past years, and the data are contained in the attached table. Complete parts a though d below. Click the icon to view the data. Click the icon to view the upper critical values of the chi-square distribution. a. Estimate the regression of house price on family income. House Price = +2.35 (Family Income) (Round to two decimal places as needed.)
Family_Income
50279
59584
55045
51042
74977
67454
70055
72642
68556
91054
85991
94797
85818
98706
119561
116103
117528
109971
115780
138694
140309
146169
145307
135844
192780
160283
166151
195679
162818
House Price($)
271765
295932
275741
268415
334833
309020
323590
331065
315057
378037
342456
375004
348564
369809
446443
449100
404612
409743
430517
440730
432046
527506
530423
486254
617824
515324
576546
569757
557909
Transcribed Image Text:Family_Income 50279 59584 55045 51042 74977 67454 70055 72642 68556 91054 85991 94797 85818 98706 119561 116103 117528 109971 115780 138694 140309 146169 145307 135844 192780 160283 166151 195679 162818 House Price($) 271765 295932 275741 268415 334833 309020 323590 331065 315057 378037 342456 375004 348564 369809 446443 449100 404612 409743 430517 440730 432046 527506 530423 486254 617824 515324 576546 569757 557909
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