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Perform a regression analysis on the information


Problem:

Imagine you are a real estate investor presented with a regression analysis of home sales in the neighborhood of one of your investment properties. Unfortunately, the report stops short of making the decision for you. Given the data as presented in those three worksheets, you need to determine:

Which is the better predictor of selling price: appraised value, square footage, or number of bedrooms?
How much value is added per $1,000 of appraised value?
How much value is added per 100 square feet?
How much value is added per bedroom?

At what price should you offer your four bedroom 2,050-square-foot investment home that has recently been appraised at $135,200?

The data for this problem comes from problem P11.1 on page 584 of your textbook. Feel free to search your local property records, change as many X values as may be available and compute the market value of your own home. If you have ever wondered how to provide evidence for the contention that home size affects electric costs you may want to take a look at a similar problem. It is another excellent example of how regression can be used to help form relationships between two variables.

What I need?

1) How do I perform a regression analysis on this information, while incorporating each of these areas?

2) The problem suggests that we change as many X values as may be available and compute the market value of your own home ($135,200). How do I do this?

Data on Recently Sold Houses in a Suburban Community






House Value Price Square_Footage Number_Bedrooms
1 119.37 121.87 20.5 4
2 148.93 150.25 22.0 4
3 130.39 122.78 15.9 3
4 135.70 144.35 18.6 3
5 126.30 116.20 12.1 2
6 137.08 139.49 17.1 3
7 123.49 115.73 16.7 3
8 150.83 140.59 17.8 3
9 123.48 120.29 15.2 4
10 132.05 147.25 18.3 2
11 148.21 152.26 17.0 3
12 139.53 144.80 17.2 3
13 114.34 107.06 16.7 3
14 140.04 147.47 16.5 3
15 136.01 135.12 16.1 2
16 140.93 140.24 15.7 3
17 132.42 129.89 16.5 4
18 118.30 121.14 16.4 3
19 122.14 111.23 14.2 2
20 149.82 145.14 20.7 4
21 128.91 139.01 16.1 2
22 134.61 129.34 19.1 4
23 121.99 113.61 14.1 2
24 150.50 141.05 18.6 4
25 142.87 152.90 19.9 4
26 155.55 157.79 22.7 5
27 128.50 135.57 19.7 4
28 143.36 151.99 18.2 3
29 119.65 120.53 16.5 3
30 122.57 118.64 14.7 2
31 145.27 149.51 18.5 4
32 149.73 146.86 21.7 4
33 147.70 143.88 19.3 3
34 117.53 118.52 13.8 2
35 140.13 146.07 18.1 3
36 136.57 135.35 17.6 3
37 130.44 121.54 15.3 2
38 118.13 132.98 17.0 3
39 130.98 147.53 19.8 4
40 131.33 128.49 15.9 2
41 141.10 141.93 17.4 3
42 117.87 123.55 17.3 3
43 160.58 162.03 21.0 5
44 151.10 157.39 20.4 4
45 120.15 114.55 17.3 2
46 133.17 139.54 16.8 2
47 140.16 149.92 20.5 4
48 124.56 122.08 17.5 3
49 127.97 136.51 18.7 4
50 101.93 109.41 13.3 2
51 131.47 127.29 17.0 3
52 121.27 120.45 14.6 2
53 143.55 151.96 19.1 3
54 136.89 132.54 16.1 2
55 106.11 114.33 14.7 2
56 137.54 141.32 18.1 3
57 134.33 83.76 16.5 2
58 127.59 118.20 15.2 2
59 137.44 140.20 19.2 4
60 114.09 113.55 14.1 2
61 145.46 156.52 20.3 3
62 141.90 137.35 19.5 3
63 116.34 110.61 13.4 2
64 149.20 153.69 18.5 3
65 141.81 153.33 17.8 3
66 116.44 111.95 14.4 2
67 137.74 143.46 20.4 4
68 144.70 142.13 21.6 5
69 149.66 155.46 21.7 4
70 118.17 135.44 17.1 2
71 137.66 127.30 16.4 3
72 119.70 113.77 13.8 2
73 143.12 141.11 21.0 5
74 129.91 130.08 16.1 2
75 141.78 139.35 19.5 4
76 159.19 160.03 20.8 5
77 156.13 152.84 19.6 3
78 126.72 122.27 19.2 4
79 133.22 145.88 19.2 4
80 118.09 115.47 14.9 2
81 141.63 135.72 16.0 2
82 138.56 136.16 16.5 3
83 134.10 144.92 18.9 4
84 132.24 131.29 16.2 3
85 145.82 138.53 18.2 3
86 127.15 124.05 17.5 3
87 105.07 107.90 14.6 2
88 127.20 123.45 15.3 3
89 111.56 111.70 15.4 2
90 150.41 145.14 19.5 3
91 129.15 120.44 14.8 3
92 130.31 136.87 20.5 4
93 129.23 140.30 16.6 3
94 105.06 113.78 15.4 2
95 134.21 141.23 17.2 3
96 109.25 104.83 14.0 2
97 127.35 118.79 15.8 3
98 104.01 112.04 17.0 3
99 133.94 137.27 18.8 4
100 141.13 145.71 18.5 3
101 136.53 138.38 14.3 2
102 118.04 109.46 13.9 2
103 153.70 144.68 21.3 4
104 126.31 133.27 18.9 4
105 134.02 133.27 16.4 2
106 141.56 150.38 20.7 3
107 142.96 135.26 18.1 3
108 118.53 112.60 14.6 2
109 121.59 114.23 14.1 2
110 146.40 153.24 21.9 4
111 141.25 125.89 15.8 3
112 130.73 135.62 18.4 3
113 132.65 138.82 19.3 3
114 125.57 129.43 19.3 4
115 125.74 136.45 18.2 3
116 120.22 126.74 14.8 2
117 128.29 130.09 16.0 2
118 136.89 132.68 18.8 3
119 142.43 142.89 17.8 3
120 119.31 127.04 19.2 3
121 120.37 131.45 18.3 4
122 118.83 114.57 14.7 2
123 124.49 129.56 16.9 3
124 140.57 149.55 19.3 4
125 133.62 140.82 19.7 2
126 105.05 111.55 15.3 2
127 147.09 142.76 20.3 5
128 115.43 124.25 18.3 3
129 125.37 132.32 20.7 3
130 115.97 121.45 16.3 2
131 125.21 132.45 15.8 3
132 130.37 135.83 17.6 3
133 119.75 125.76 18.1 4
134 120.93 125.84 17.1 3
135 126.80 135.32 18.9 3
136 118.82 120.14 16.4 2
137 144.08 147.53 20.1 4
138 142.49 144.94 17.3 3
139 140.55 136.01 17.7 4
140 130.36 119.33 17.5 4
141 124.27 131.15 16.6 3
142 167.73 172.36 25.1 5
143 129.19 137.17 17.0 2
144 125.18 124.71 16.6 3
145 157.51 148.65 21.1 4
146 126.67 128.52 14.3 2
147 137.57 132.02 17.1 4
148 133.46 128.03 15.8 2
149 163.57 168.06 23.5 5
150 118.46 114.92 14.2 2

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