Using the accompanying Home Market Value data, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. State the model and explain R² Click the icon to view the Home Market Value data. State the model for predicting MarketValue as a function of Age and Size, where Age is the age of the house, and Size is the size of the house in square feet. MarketValue=44813.390 + (-643.592) Age+ (39.011) Size (Type integers or decimals rounded to three decimal places as needed.) The value of R2, 0.546, indicates that 54.58 % of the variation in the dependent variable is explained by these independent variables. (Type integers or decimals rounded to three decimal places as needed.) House Age Square Feet Market Value 31 1874 91260 32 1833 101224 30 1827 93611 34 1840 87865 33 1919 106806 32 2102 112411 32 1727 84077 35 1854 92782 33 1811 85668 34 1600 89260 32 1850 100893 33 1638 99736 34 1649 84310 32 2261 110753 30 2459 117449 33 1593 91412 30 2020 114127 34 1551 91056 34 1736 85188 30 1708 86978 28 1460 84159 26 1461 80632 29 1509 80140 27 1653 86827 28 1492 79635 29 1424 82010 27 1590 86135 27 1689 92751 27 1552 78353 28 1473 90369 27 1481 88912 26 1493 90103 28 1556 74762 28 1530 80507 26 1713 88691 28 1548 80560 28 1703 95756 28 1482 83700 26 1590 104405 29 1515 83155 28 1748 96708 26 1587 114973
Using the accompanying Home Market Value data, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. State the model and explain R² Click the icon to view the Home Market Value data. State the model for predicting MarketValue as a function of Age and Size, where Age is the age of the house, and Size is the size of the house in square feet. MarketValue=44813.390 + (-643.592) Age+ (39.011) Size (Type integers or decimals rounded to three decimal places as needed.) The value of R2, 0.546, indicates that 54.58 % of the variation in the dependent variable is explained by these independent variables. (Type integers or decimals rounded to three decimal places as needed.) House Age Square Feet Market Value 31 1874 91260 32 1833 101224 30 1827 93611 34 1840 87865 33 1919 106806 32 2102 112411 32 1727 84077 35 1854 92782 33 1811 85668 34 1600 89260 32 1850 100893 33 1638 99736 34 1649 84310 32 2261 110753 30 2459 117449 33 1593 91412 30 2020 114127 34 1551 91056 34 1736 85188 30 1708 86978 28 1460 84159 26 1461 80632 29 1509 80140 27 1653 86827 28 1492 79635 29 1424 82010 27 1590 86135 27 1689 92751 27 1552 78353 28 1473 90369 27 1481 88912 26 1493 90103 28 1556 74762 28 1530 80507 26 1713 88691 28 1548 80560 28 1703 95756 28 1482 83700 26 1590 104405 29 1515 83155 28 1748 96708 26 1587 114973
Chapter1: Financial Statements And Business Decisions
Section: Chapter Questions
Problem 1Q
Related questions
Question
It says the percent is wrong what is the right solution?
Transcribed Image Text:Using the accompanying Home Market Value data, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. State the model and explain R²
Click the icon to view the Home Market Value data.
State the model for predicting MarketValue as a function of Age and Size, where Age is the age of the house, and Size is the size of the house in square feet.
MarketValue=44813.390 + (-643.592) Age+ (39.011) Size
(Type integers or decimals rounded to three decimal places as needed.)
The value of R2, 0.546, indicates that 54.58 % of the variation in the dependent variable is explained by these independent variables.
(Type integers or decimals rounded to three decimal places as needed.)
Transcribed Image Text:House Age Square Feet
Market Value
31
1874
91260
32
1833
101224
30
1827
93611
34
1840
87865
33
1919
106806
32
2102
112411
32
1727
84077
35
1854
92782
33
1811
85668
34
1600
89260
32
1850
100893
33
1638
99736
34
1649
84310
32
2261
110753
30
2459
117449
33
1593
91412
30
2020
114127
34
1551
91056
34
1736
85188
30
1708
86978
28
1460
84159
26
1461
80632
29
1509
80140
27
1653
86827
28
1492
79635
29
1424
82010
27
1590
86135
27
1689
92751
27
1552
78353
28
1473
90369
27
1481
88912
26
1493
90103
28
1556
74762
28
1530
80507
26
1713
88691
28
1548
80560
28
1703
95756
28
1482
83700
26
1590
104405
29
1515
83155
28
1748
96708
26
1587
114973
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