13.76 The data on air pollution are from Sokal and Rohlf (1981), Biometry. The following data are on air pollution in 41 U.S. cities. The type of air pollution under study is the annual mean con- centration of sulfur dioxide. The values of six explanatory variables were recorded in order to ex- amine the variation in the sulfur dioxide concentrations. They are as follows: y = the annual mean concentration of sulfur dioxide (micrograms per cubic meter) x₁ = average annual temperature in °F x₂ = number of manufacturing enterprises employing 20 or more workers x3 = population size (1970) census (thousands) X4 = average annual wind speed (mph) x5 = average annual precipitation (inches)
13.76 The data on air pollution are from Sokal and Rohlf (1981), Biometry. The following data are on air pollution in 41 U.S. cities. The type of air pollution under study is the annual mean con- centration of sulfur dioxide. The values of six explanatory variables were recorded in order to ex- amine the variation in the sulfur dioxide concentrations. They are as follows: y = the annual mean concentration of sulfur dioxide (micrograms per cubic meter) x₁ = average annual temperature in °F x₂ = number of manufacturing enterprises employing 20 or more workers x3 = population size (1970) census (thousands) X4 = average annual wind speed (mph) x5 = average annual precipitation (inches)
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13.76 The data on air pollution are from Sokal and Rohlf (1981), Biometry. The following data
are on air pollution in 41 U.S. cities. The type of air pollution under study is the annual mean con-
centration of sulfur dioxide. The values of six explanatory variables were recorded in order to ex-
amine the variation in the sulfur dioxide concentrations. They are as follows:
City
1
2
3
4
5
6
7
8
9
10
11
12
City
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
y = the annual mean concentration of sulfur dioxide (micrograms per cubic meter)
x₁ = average annual temperature in °F
x₂ = number of manufacturing enterprises employing 20 or more workers
x3 = population size (1970) census (thousands)
X4 = average annual wind speed (mph)
xs = average annual precipitation (inches)
x6 = average number of days with precipitation per year
y
10
13
12
17
56
36
29
14
10
24
110
28
y
17
x1
8
30
9
70.3
61.0
56.7
51.9
49.1
54.0
57.3
68.4
75.5
61.5
50.6
52.3
49.0
56.6
55.6
68.3
47
55.0
35
49.9
29
43.5
14
54.5
56
55.9
14
51.5
11
56.8
46
47.6
11
47.1
23
54.0
65
49.7
26
51.5
69
54.6
61
50.4
94
50.0
10
61.6
18
59.4
9
66.2
10
68.9
28 51.0
31
59.3
26
57.8
29
51.1
31
55.2
16
45.7
X1
X₂
213
91
453
454
412
80
434
136
207
368
3,344
361
x2
X3
275
641
721
137
96
197
379
35
569
582
6.0
132
8.2
716
8.7
515
9.0
158
9.0
80
9.0
757
9.3
529
8.8
335
9.0
497
9.1
3,369 10.4
746
9.7
x3
104
201
125
277
291
593
204
361
625
905
1,064 1,513
699
744
381
507
775
622
181
347
46
244
44
391
462
1,007
266
1,692
347
343
337
116
463
453
X4
751
540
1,950
520
179
624
448
844
1,233
176
308
299
531
71
717
X4
11.2
12.7
8.3
8.4
9.6
10.1
10.6
10.0
9.5
10.9
8.9
8.8
12.4
7.1
10.9
8.6
9.6
9.4
10.6
9.2
7.9
10.9
10.8
8.7
10.6
7.6
9.4
6.5
11.8
X5
7.05
48.52
20.66
12.95
43.37
40.25
38.89
54.47
59.80
48.34
34.44
38.74
X5
30.85
30.58
43.11
56.77
41.31
30.96
25.94
37.00
35.89
30.18
7.77
33.36
36.11
39.04
34.99
37.01
39.93
36.22
42.75
49.10
46.00
35.94
48.19
15.17
44.68
42.59
38.79
40.75
29.07
X6
36
100
67
86
127
114
111
116
128
115
122
121
x6
103
82
123
113
111
129
137
99
105
98
58
135
166
132
155
134
115
147
125
105
119
78
103
89
116
115
164
148
123
Develop the most appropriate multiple regression model to predict the y value. Be sure to perform a
thorough residual analysis. In
an
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