The SAS
System 1
hs
Obs sn income
GPA SAT cGPA coyrs evaluation tcoyrs
1 1 48640
1.70 1196 2.90
27.8 82.44 5.27257
2 2 40624
2.42 1243 3.06
7.3 66.09 2.70185
3 3 34898
3.24 1187 3.48
1.7 68.32 1.30384
4 4 39069
3.10 1070 2.99
10.3 67.25 3.20936
5 5 36800
2.29 1120 3.10
9.2 64.55 3.03315
6 6 43389
2.18 1148 3.12
14.4 80.25 3.79473
7 7 43423
2.42 1115 3.07
17.4 73.73 4.17133
8 8 38594
3.25 1148 3.28
11.3 54.68 3.36155
9 9 37549
2.40 1026 3.26
8.3 79.29 2.88097
10 10 39564
2.91 1078 3.40
14.1 64.83 3.75500
11 11 42738
2.21 1317 3.13
12.6 67.25 3.54965
12 12 36049
3.75 1038 3.32
9.4 53.42 3.06594
13 13 34933
2.95 1002 3.12
3.8 77.50 1.94936
14 14 38913
1.96 1054 2.84
15.2 62.84 3.89872
15 15 36021
2.06 1146 2.71
1.6 76.46 1.26491
16 16 41591
1.68 1244 2.89
4.8 78.69 2.19089
17 17 34726
2.77 967 3.40
7.7 67.09 2.77489
18 18 38861
2.27 1189 3.04
13.0 55.19 3.60555
19 19 28477
2.92 835 3.14
2.0 69.53 1.41421
20 20 38804 2.07
1139 2.57 8.2
67.37 2.86356
21 21 40013
3.30 949 3.22
10.0 80.48 3.16228
22 22 36933
1.80 1026 2.81
6.2 76.52 2.48998
23 23 40201
3.01 1364 3.32
8.8 48.09 2.96648
24 24 37044
2.58 1203 3.02
9.5 51.10 3.08221
25 25 31470
1.72 846 2.94
3.7 65.84 1.92354
26 26 44923
3.12 1078 3.61
23.8 77.52
4.87852
27 27 43957
2.86 1192 2.93
14.4 79.75 3.79473
28 28 36681
3.36 943 3.40
6.7 67.12 2.58844
29 29 39461
2.68 1266 3.23
9.7 66.27 3.11448
30 30 46532
2.25 1036 2.74
37.0 66.96 6.08276
31 31 42243
1.87 1056 2.91
12.7 83.48 3.56371
32 32 38264
2.16 1204 3.17
6.7 63.18 2.58844
33 33 40234
2.03 1143 2.92
13.0 68.77 3.60555
34 34 47567
2.43 1253 3.28
15.6 85.64 3.94968
35 35 38956
2.16 962 2.86
14.5 76.66 3.80789
36 36 42061
2.57 1136 2.99
11.5 75.97 3.39116
37 37 43943
1.94 1105 2.96
20.3 77.31 4.50555
38 38 35736
2.27 989 3.20
4.9 76.05 2.21359
39 39 41491
1.08 1257 2.82
10.0 69.37
3.16228
40 40 40821
1.85 1198 2.79
4.5 84.55 2.12132
41 41 45078
1.88 1185 2.90
15.3 73.12 3.91152
42 42 48144
2.24 1318 3.12
19.5 69.88 4.41588
43 43 43792
2.42 1281 3.00
16.7 61.63 4.08656
44 44 42696
1.92 1056 2.85
11.7 81.12 3.42053
45 45 38037
2.71 999 3.47
7.9 77.60 2.81069
46 46 35978
2.22 1069 2.92
3.5 76.12 1.87083
47 47 36366
2.13 855 2.75
18.5 66.26 4.30116
48 48 44142
2.03 1075 2.83
25.6 66.93 5.05964
49 49 34816
0.46 1067 2.32
3.1 72.21 1.76068
50 50 39879
3.74 1048 3.97
15.5 72.58 3.93700
51 51 36287
2.58 935 3.28
11.8 56.08 3.43511
52 52 46177
2.94 1032 3.46
30.0 73.59 5.47723
53 53 35214
2.05 1121 2.82
2.8 67.97 1.67332
54 54 28198
2.40 907 3.24
1.8 58.04 1.34164
55 55 31356
2.21 1069 3.28
3.6 59.26 1.89737
56 56 35622
2.07 1057 2.83
5.2 70.93 2.28035
57 57 41313
2.02 1151 2.79
16.5 67.62 4.06202
58 58 36101
2.68 975 3.16
10.0 64.78 3.16228
59 59 37343
2.70 1144 3.19
6.7 69.55 2.58844
60 60 39032
2.73 1128 3.17
9.1 70.74 3.01662
61 61 48542
2.84 1163 3.26
33.5 68.48 5.78792
62 62 36906
2.14 1179
3.16 3.0 71.98 1.73205
63 63 40445
2.37 1084 3.06
13.1 72.22 3.61939
64 64 39434
3.34 1120 3.40
12.7 64.72 3.56371
65 65 39208
3.54 967 3.36
14.9 77.65 3.86005
66 66 41522
2.57 1161 3.35
15.4 61.10 3.92428
67 67 40124
2.99 1176 3.42
8.3 68.24 2.88097
68 68 42416
2.98 1197 3.38
8.6 78.39 2.93258
69 69 30772
2.98 977 3.42
0.3 72.54 0.54772
70 70 42868
2.02 1137 2.94
18.1 62.55 4.25441
71 71 42662
1.77 1185 3.08
16.9 63.17 4.11096
The SAS System 2
hs
Obs sn income
GPA SAT cGPA coyrs evaluation tcoyrs
72 72 41525
2.26 1080 2.65
9.2 85.00 3.03315
73 73 42154
2.54 1119 3.14
19.1 67.88 4.37035
74 74 39215
2.55 1036 2.95
17.4 68.76 4.17133
75 75 45773 2.63
1166 2.97 26.3
73.97 5.12835
76 76 43388
2.03 1238 2.71
20.9 53.62 4.57165
77 77 40282
2.38 1102 2.85
11.3 71.31 3.36155
78 78 44462
2.91 1117
3.16 22.5 73.20 4.74342
79 79 33693
2.60 908 2.99
5.8 63.70 2.40832
80 80 38791
2.26 1154 3.24
7.6 74.06 2.75681
81 81 44734
2.78 1064 3.12
23.2 76.21 4.81664
82 82 42003
1.96 1076 2.91
22.1 66.03 4.70106
83 83 44269
2.34 1169 2.92
19.1 68.06 4.37035
84 84 42236
2.36 1034 3.03
14.7 78.62
3.83406
85 85 48139
2.08 1276 2.97
22.6 74.60 4.75395
86 86 45789
3.44 1207 3.45
17.1 76.29 4.13521
87 87 37160
3.55 1088 3.36
6.8 69.25 2.60768
88 88 45106
3.16 1155 3.44
22.4 77.50 4.73286
89 89 39023
1.38 1199 2.71
9.2 57.23 3.03315
90 90 37390
2.21 999 2.91
14.1 60.42 3.75500
91 91 46177 2.99
1176 3.34 15.3
85.33 3.91152
92 92 41086
2.69 1129 3.11
14.1 66.71 3.75500
93 93 43262
3.46 1156 3.51
22.4 59.65 4.73286
94 94 38619
2.84 1152
3.30 9.6 70.62 3.09839
95 95 37428
3.13 1114 3.42
9.6 54.56 3.09839
96 96 47050
2.26 1247 3.02
16.1 81.74 4.01248
97 97 41497
2.38 1166 2.83
9.7 74.91 3.11448
98 98 38878
2.23 1249 2.80
3.5 78.06 1.87083
99 99 46391
3.33 1111 3.31
28.8 71.01 5.36656
100 100 40754 2.24
1072 3.13 9.9
80.08 3.14643
101 101 37417 2.69
1164 2.90 6.8
65.45 2.60768
102 102 40191 2.17
1122 3.02 11.2
74.09 3.34664
103 103 36183 2.61
1099 3.37 6.4
65.13 2.52982
104 104 42131 1.72
1053 2.97 26.3
59.95 5.12835
105 105 43130 2.17
1070 3.01 21.8
70.72 4.66905
106 106 42167 2.64
867 2.99 20.9
83.68 4.57165
107 107 41733 3.16
1213 3.29 13.0
64.15 3.60555
108 108 40179 2.55
907 3.23 26.2
68.71 5.11859
109 110 40062
2.55 1079 3.29
10.4 80.68 3.22490
110 111 47664
2.60 1267
3.08 17.7 91.28 4.20714
111 112 40127
2.78 1024 3.25
12.5 78.31 3.53553
112 113 41683
1.61 1162 2.67
16.3 67.65 4.03733
113 114 33181
3.05 1110 3.41
3.7 62.78 1.92354
114 115 43244
1.52 1172 2.58
18.0 70.65 4.24264
115 116 32370
1.93 980 3.03
3.0 66.82 1.73205
116 117 44515
2.68 1095 2.98
22.3 82.34
4.72229
117 118 34931
2.23 1063 3.04
5.7 60.36 2.38747
118 119 40011
3.03 1041 3.15
16.4 66.38 4.04969
119 120 45250
2.12 1237 2.97
20.2 68.98 4.49444
120 121 41903
2.55 959 3.09
26.7 71.13 5.16720
121 122 38320
2.39 1091 3.14
8.2 68.26 2.86356
122 123 42932
2.64 1083 3.29
18.2 74.77 4.26615
123 124 37456
2.50 925 3.34
13.5 68.02 3.67423
124 125 43057
2.64 1100 3.19
12.4 80.01 3.52136
125 126 41194
3.64 1196 3.37
5.9 77.33 2.42899
126 127 37850
1.88 991
2.91 9.9 64.01 3.14643
127 128 38961
1.25 979 2.83
8.5 72.32 2.91548
128 129 41686
1.98 1202 2.81
9.7 77.69 3.11448
129 130 39894
3.32 1028 3.32
16.1 72.88 4.01248
130 131 42017
2.75 1026 3.27
26.3 67.22 5.12835
131 132 43604
2.43 1201 3.12
22.8 54.48 4.77493
132 133 41151
2.63 1120 3.11
18.8 64.03
4.33590
133 134 42929
2.54 988 3.07
21.6 67.67 4.64758
134 135 39742
2.82 1049 3.33
16.6 62.97 4.07431
135 136 38811
2.47 969 3.06
10.4 80.68 3.22490
136 137 42379
2.74 1210 3.19
12.9 74.77 3.59166
137 138 37305
2.11 904 2.96
17.3 55.88 4.15933
138 139 36304
3.29 1054 3.54
6.5 68.27 2.54951
139 140 41014
1.02 1168 2.64
9.5 70.44 3.08221
140 141 34858
2.35 1023 2.88
4.2 64.27 2.04939
141 142 40557
2.02 1167 3.16
17.6 53.35 4.19524
142 143 41138
2.02 1072
2.78 12.5 84.05 3.53553
The SAS
System 3
hs
Obs sn income
GPA SAT cGPA coyrs evaluation tcoyrs
143 144 30330
3.40 1102 3.50
1.1 57.60 1.04881
144 145 35994
1.05 1014 2.65
10.6 54.14 3.25576
145 146 34642
2.12 965
2.85 3.5 68.04 1.87083
146 147 37012
2.94 1090 3.40
13.3 50.83 3.64692
147 148 42258
2.64 1132 3.18
13.7 76.81 3.70135
148 149 34077
2.53 961 3.09
3.6 69.84 1.89737
149 150 35649
2.94 1218 3.23
3.3 63.94 1.81659
150 151 41145
2.40 1026 3.21
16.5 76.29 4.06202
151 152 33188
2.95 1061 3.18
0.9 74.75 0.94868
152 153 37999
1.98 1157 2.85
6.7 68.56 2.58844
153 154 34255
3.48 957 3.50
13.7 49.58 3.70135
154 155 35193
3.30 1028 3.56
8.9 60.71 2.98329
155 156 38148
2.39 1059 3.10
15.1 62.21 3.88587
156 157 38384
2.41 1173 3.02
8.8 59.59 2.96648
157 158 42202
3.10 1165 3.37
11.7 72.37 3.42053
158 159
40867 2.51 1118
3.13 20.4 55.16 4.51664
159 160 42918
3.28 1055 3.22
16.3 72.07 4.03733
160 161 39402
2.32 1002 3.09
15.8 62.91 3.97492
161 162 42609
3.36 1193
3.33 9.6 74.94 3.09839
162 163 37356
2.56 1247 3.13
2.9 71.54 1.70294
163 164 40276
3.34 1136 3.26
9.5 70.37 3.08221
164 165 41032
1.69 1330 2.89
5.8 77.67 2.40832
165 166 38647
2.26 918 3.17
11.8 75.66 3.43511
166 167 42340
2.24 1107 3.18
11.0 74.45 3.31662
167 168 43785
1.65 1168 2.63
12.0 74.22 3.46410
168 169 41218
2.27 1019 2.64
20.8 64.07 4.56070
169 170 47834
2.93 978 3.14
33.9 84.74 5.82237
170 171 34350
3.11 938 3.37
6.1 65.62 2.46982
171 172 37293
1.44 1035 2.49
6.1 71.22 2.46982
172 173 37461
1.95 1037 2.81
5.6 75.19 2.36643
173 174 51341
3.11 1177 3.56
40.7 78.96 6.37966
174 175
36055 3.48 1051
3.42 5.0 79.71 2.23607
175 176 35499
2.21 913 2.82
10.6 73.10 3.25576
176 177 40852
3.12 1140 3.35
14.8 69.07 3.84708
177 178 44598
2.30 1176
3.04 19.3 69.34 4.39318
178 179 45455
2.20 1067 2.89
14.8 99.06 3.84708
179 180 34753
2.78 886 2.99
9.0 74.00 3.00000
180 181 38512
2.66 1356 3.13
5.1 61.20 2.25832
181 182 35697
3.45 954 3.34
5.8 73.45 2.40832
182 183 44784
3.26 1267 3.48
11.7 69.48 3.42053
183 184 42151
2.06 1061 3.08
16.7 73.18 4.08656
184 185 41244
3.80 1013 3.70
15.0 73.16 3.87298
185 186 41451
2.30 1013 3.10
22.6 63.00 4.75395
186 187 44168
1.81 1141 2.81
16.5 74.44 4.06202
187 188 37125
1.45 1022 2.58
12.0 65.60 3.46410
188 189 38917
2.96 1146 3.27
5.5 71.83 2.34521
189 190 44552
2.69 1117 3.29
22.4 74.26 4.73286
190 191
40673 2.67 1279
2.96 9.0 70.03 3.00000
191 192 40842
2.43 993 3.15
17.1 75.49 4.13521
192 193 39442
2.64 906 3.23
17.0 64.14 4.12311
193 194 39445
2.46 1263
2.86 7.6 55.88 2.75681
194 195 41298
2.59 1086 3.27
22.0 57.84 4.69042
195 196 37725
1.06 1014 2.34
17.0 53.71 4.12311
196 197 37356
1.48 1047 2.46
6.6 69.79 2.56905
197 198 41817
2.76 994 3.09
26.4 68.81 5.13809
198 199 39697
2.95 1179 2.86
3.8 79.44 1.94936
199 200 41826
3.67 1324 3.53
7.7 79.81 2.77489
Scatterplots for All Variables by Income 4
Plot of income*hsGPA. Legend: A = 1 obs,
B = 2 obs, etc.
income ‚
‚
52000 ˆ
‚
‚ A
‚
‚
50000 ˆ
‚
‚
‚ A
‚ A
48000 ˆ A A A
‚ A A
‚ A
‚
‚ A A
46000 ˆ AA
‚ A A A
‚ A A A
‚ A A A
‚ AA B A
44000 ˆ A AA A
‚ A C
‚ A A AA A
A
‚ A AA A
AA AA
‚ A A A AA AA
42000 ˆ A A A CA B A
‚ A AA
A BA A
A
‚ A
A
B A A
AAA A A
‚ A A BA A A
‚ B B A
A
40000 ˆ A B A
B B A
‚ A A AAA B A
‚ A A A A A
‚ A A AAAC A AA
‚ A AA A
A
38000 ˆ A A A A
‚ A A AA A
A
‚ BA AA
B A A A
‚ A A A A
‚ A A A
36000 ˆ A A A AA A
A
‚ A AA A
A
‚ A A
‚ A AA A B A
A
‚ A A
34000 ˆ A
‚ A
‚ A A
‚
‚ A
32000 ˆ
‚ A
‚ A
‚ A
‚ A
30000 ˆ
‚
‚
‚
‚ A
28000 ˆ A
‚
Šƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒ
0 1 2 3 4
hsGPA
Scatterplots for All Variables by Income 5
Plot of
income*SAT. Legend: A = 1 obs, B = 2 obs, etc.
income ‚
‚
52000 ˆ
‚
‚ A
‚
‚
50000 ˆ
‚
‚
‚ A
‚ A
48000 ˆ A A A
‚ AA
‚
A
‚
‚ A A
46000 ˆ A A
‚ A A A
‚ A A A
‚ A A A
‚ A B B
44000 ˆ A A A A
‚ A A A A
‚ A A AA A
A
‚ A B A
A
AA A
‚ A A A A A AA
42000 ˆ A A A A AAA A A A
‚ A A C
AA AA
‚ AAA AA AA AA A
A
‚ A A A A A A A
‚ A A AA A A
40000 ˆ A
A
B B
A A A
‚ A A A A A A B
‚ A A A A A
‚ A AAA
A AAB A A
‚ A A A A A
38000 ˆ AA A
A
‚ A AAA A
A
‚ A A A AA B A
A A
‚ A A A A
‚ A
A
A
36000 ˆ A A A A A
A
A
‚ A A A A A
‚ A A
‚ A
B A A B
A
‚ A A
34000 ˆ A
‚ A
‚ A A
‚
‚ A
32000 ˆ
‚ A
‚ A
‚ A
‚ A
30000 ˆ
‚
‚
‚
‚ A
28000 ˆ A
‚
Šƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒ
800 900 1000 1100 1200 1300 1400
SAT
Scatterplots for All Variables by Income 6
Plot of income*cGPA. Legend: A = 1 obs,
B = 2 obs, etc.
income ‚
‚
52000 ˆ
‚
‚ A
‚
‚
50000 ˆ
‚
‚
‚ A
‚ A
48000 ˆ A AA
‚ A A
‚ A
‚
‚ A A
46000 ˆ A A
‚ A A A
‚ A A A
‚ A A A
‚ AA A A A
44000 ˆ B AA
‚ A A AA
‚ A A A A A A
‚ A A B A A AA
‚ A A C
AA
42000 ˆ A AB
‚ AA C A
A A A
‚ B B A B A
A A A
‚ A A A
C A
‚ A A A A A A
40000 ˆ A A
BAAA A A
‚ B A B
A B
‚ A AA
A A
‚ A AAB
AA A AB
‚ A BA A
38000 ˆ AA A A
‚ A A A A A A
‚ AA A A A A AA AA
‚ A AA
A
‚ A A A
36000 ˆ A A A A AA A
‚ B B A
‚ A A
‚ A AA AA A A A
‚ A A
34000 ˆ A
‚ A
‚ A A
‚
‚ A
32000 ˆ
‚ A
‚ A
‚ A
‚ A
30000 ˆ
‚
‚
‚
‚ A
28000 ˆ A
‚
Šƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒ
2.0 2.5 3.0 3.5 4.0
cGPA
Scatterplots for All Variables by Income 7
Plot of income*coyrs. Legend: A = 1 obs,
B = 2 obs, etc.
income ‚
‚
52000 ˆ
‚
‚
A
‚
‚
50000 ˆ
‚
‚
‚ A
‚ A
48000 ˆ A A A
‚ A A
‚ A
‚
‚ A A
46000 ˆ A A
‚ A A A
‚ A A A
‚ A AA
‚ B C
44000 ˆ A A A A
‚ A AA
A
‚ A A A AAA
‚ A AA
AA B A
‚ A AA BAA
42000 ˆ A
A A A A A CA
‚ A
AC A AA A
‚ B
A A A AB
A A
A
‚ A A AA
A A A
‚ AA A B
A
40000 ˆ A AAAA AB
A
‚ A
A A AA AB
‚ BA A A
‚ A A
‚ A A B A
38000 ˆ AA A
A
‚ A A AA A A
‚ A
AC A AAA
A
‚ A
AA A
‚ A
A
A
36000 ˆ A A AA AAA
‚ A AAA
A
‚ A A
‚ A AC A A A
‚ A A
34000 ˆ A
‚ A
‚ A A
‚
‚ A
32000 ˆ
‚ A
‚ A
‚ A
‚ A
30000 ˆ
‚
‚
‚
‚ A
28000 ˆ A
‚
Šƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒ
0 10 20 30 40 50
coyrs
Scatterplots for All Variables by Income 8
Plot of income*tcoyrs. Legend: A = 1 obs,
B = 2 obs, etc.
income
‚
‚
52000 ˆ
‚
‚
A
‚
‚
50000 ˆ
‚
‚
‚
A
‚ A
48000 ˆ A A A
‚ A A
‚ A
‚
‚ A A
46000 ˆ A A
‚ A A A
‚ A A A
‚ A AA
‚ AA C
44000 ˆ A A A A
‚ A AA
A
‚ A A A AAA
‚ A AA
AAB A
‚ A AABA A
42000 ˆ A A A A AA CA
‚ A AC
A AA A
‚ B A A AA B A AA
‚ A A AA A A A
‚ AA A AA A
40000 ˆ A AAA A AB A
‚ A A A A A AB
‚ B A A A
‚ A A AB AA AA AA
‚ A A AA A
38000 ˆ A A
A
A
‚ A A
A A A A
‚ A AC
A A AA A
‚ A AA
A
‚ A A A
36000 ˆ A A A A BA
‚ A AAA
A
‚ A A
‚ A AAB A
A A
‚ A A
34000 ˆ A
‚ A
‚ A A
‚
‚ A
32000 ˆ
‚ A
‚ A
‚ A
‚ A
30000 ˆ
‚
‚
‚
‚ A
28000 ˆ A
‚
Šƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒ
0 1
2 3 4
5 6 7
tcoyrs
Scatterplots for All Variables by Income 9
Plot of income*evaluation.
Legend: A = 1 obs, B = 2 obs,
etc.
income ‚
‚
52000 ˆ
‚
‚ A
‚
‚
50000 ˆ
‚
‚
‚ A
‚ A
48000 ˆ A A A
‚
A A
‚ A
‚
‚ A A
46000 ˆ A A
‚ A A A
‚ A A A
‚ A AA
‚ AA AA A
44000 ˆ A A A A
‚ A A AA
‚ A A B
B
‚ B B A B
A
‚ A B A
B A
42000 ˆ A AAAA A A A A A
‚ A A
A A A A A A A
‚ A B AA
A A AB
A
‚ A A
AA A A A
‚ A
A AAAA
40000 ˆ A AA BA A B
‚ A B
C A A
‚ A A A A A
‚ A A A AAAA AA A A
‚ A AA A
A
38000 ˆ A A A A
‚ AA A A A A
‚ B A A A ABAA
‚ A A A A
‚ A A A
36000 ˆ AA AA B
A
‚ A
A AA A
‚ A A
‚ A A AB A A A
‚ A A
34000 ˆ A
‚ A
‚ A A
‚
‚ A
32000 ˆ
‚ A
‚ A
‚ A
‚ A
30000 ˆ
‚
‚
‚
‚ A
28000 ˆ A
‚
Šƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒ
40 50 60 70 80 90 100
evaluation
Correlations for All Variables 10
The CORR Procedure
7 Variables: income
hsGPA
SAT cGPA coyrs
tcoyrs evaluation
Simple Statistics
Variable N Mean Std Dev Sum
income
199 40027 3960 7965308
hsGPA 199 2.49704 0.58565 496.91000
SAT 199 1097 106.45612 218249
cGPA 199 3.09432 0.26251 615.77000
coyrs 199 12.96080 7.39531 2579
tcoyrs 199 3.44174 1.05870 684.90664
evaluation
199 69.89101 8.39628 13908
Simple Statistics
Variable Minimum Maximum
income 28198 51341
hsGPA 0.46000 3.80000
SAT 835.00000 1364
cGPA 2.32000 3.97000
coyrs 0.30000 40.70000
tcoyrs 0.54772 6.37966
evaluation 48.09000 99.06000
Pearson Correlation Coefficients, N = 199
Prob > |r| under H0:
income
hsGPA
SAT cGPA
income 1.00000 -0.01281 0.47048 -0.01196
0.8575 <.0001 0.8668
hsGPA -0.01281 1.00000 -0.03004 0.83016
0.8575 0.6736 <.0001
SAT 0.47048 -0.03004 1.00000 -0.01363
<.0001 0.6736 0.8485
cGPA -0.01196 0.83016 -0.01363 1.00000
0.8668 <.0001 0.8485
coyrs 0.76087 0.02945 -0.00473 0.04728
<.0001 0.6797 0.9472 0.5072
Pearson Correlation Coefficients, N = 199
Prob > |r| under H0:
coyrs tcoyrs evaluation
income
0.76087 0.78503 0.38564
<.0001 <.0001 <.0001
hsGPA 0.02945 0.01445 0.00759
0.6797 0.8394 0.9152
SAT -0.00473 0.01655 0.01771
0.9472 0.8165 0.8040
cGPA 0.04728 0.03305 -0.03989
0.5072 0.6431 0.5759
coyrs 1.00000 0.97883 0.03699
<.0001 0.6040
Correlations for All Variables 11
The CORR
Procedure
Pearson Correlation Coefficients, N = 199
Prob > |r| under H0:
income
hsGPA
SAT cGPA
tcoyrs 0.78503 0.01445 0.01655 0.03305
<.0001 0.8394 0.8165 0.6431
evaluation
0.38564 0.00759 0.01771 -0.03989
<.0001 0.9152 0.8040 0.5759
Pearson Correlation Coefficients, N = 199
Prob > |r| under H0:
coyrs tcoyrs evaluation
tcoyrs 0.97883 1.00000 0.02799
<.0001 0.6948
evaluation
0.03699 0.02799 1.00000
0.6040 0.6948
Regression of Income by CoYrs 12
The REG Procedure
Model: MODEL1
Dependent Variable: income
Analysis of Variance
Sum of Mean
Source
DF Squares Square F Value
Pr > F
Model
1 1913818429 1913818429 316.39
<.0001
Error
197 1191628685 6048877
Corrected Total
198 3105447114
Root
MSE 2459.44640 R-Square
0.6163
Dependent Mean 40027 Adj R-Sq 0.6143
Coeff Var
6.14452
Parameter
Estimates
Parameter Standard
Variable DF
Estimate Error t Value
Pr > |t|
Intercept 1
29920 594.35675 50.34
<.0001
tcoyrs 1
2936.59619 165.09398 17.79
<.0001
Chrissy Regression by CoYrs
and SAT 13
The REG Procedure
Model: MODEL1
Dependent Variable: income
Analysis of
Variance
Sum of Mean
Source
DF Squares Square F Value
Pr > F
Model
2 2563964541 1281982271 464.04
<.0001
Error
196 541482572 2762666
Corrected Total
198 3105447114
Root
MSE 1662.12701 R-Square
0.8256
Dependent Mean 40027 Adj R-Sq 0.8239
Coeff Var 4.15255
Parameter
Estimates
Parameter Standard
Variable DF
Estimate Error t Value
Pr > |t|
Intercept 1
11346 1275.61716 8.89
<.0001
tcoyrs 1
2908.26775 111.58801 26.06
<.0001
SAT 1 17.02400 1.10974 15.34
<.0001
Chrissy Regression by CoYrs, SAT,
and Evaluation 14
The REG Procedure
Model: MODEL1
Dependent Variable: income
Analysis of
Variance
Sum of Mean
Source
DF Squares Square F Value
Pr > F
Model
3 2957482362 985827454 1299.20
<.0001
Error
195 147964752 758794
Corrected Total
198 3105447114
Root
MSE 871.08760 R-Square
0.9524
Dependent Mean 40027 Adj R-Sq 0.9516
Coeff Var 2.17627
Parameter
Estimates
Parameter Standard
Variable DF
Estimate Error t Value
Pr > |t|
Intercept 1
-17.26913 834.22238 -0.02
0.9835
tcoyrs 1
2871.36184 58.50350 49.08
<.0001
SAT 1 16.79548 0.58168 28.87
<.0001
evaluation 1 167.99551 7.37696 22.77
<.0001
Chrissy Regression by CoYrs, SAT,
Evaluation, and hsGPA 15
The REG Procedure
Model: MODEL1
Dependent Variable: income
Analysis of Variance
Sum of Mean
Source
DF Squares Square F Value
Pr > F
Model
4 2958011250 739502812 973.06
<.0001
Error
194 147435864 759979
Corrected Total
198 3105447114
Root
MSE 871.76756 R-Square
0.9525
Dependent Mean 40027 Adj R-Sq 0.9515
Coeff Var
2.17797
Parameter
Estimates
Parameter Standard
Variable DF
Estimate Error t Value
Pr > |t|
Intercept 1
213.62899 879.55823 0.24
0.8084
tcoyrs 1
2872.08195 58.55553 49.05
<.0001
SAT 1 16.78070 0.58240 28.81
<.0001
evaluation 1 168.04305 7.38294 22.76
<.0001
hsGPA 1
-88.30100 105.84847 -0.83
0.4052
Chrissy Regression by All Variables 16
The REG Procedure
Model: MODEL1
Dependent Variable: income
Analysis of
Variance
Sum of Mean
Source
DF Squares Square F Value
Pr > F
Model
5 2958391034 591678207 776.53
<.0001
Error
193 147056079 761949
Corrected Total
198 3105447114
Root
MSE 872.89667 R-Square
0.9526
Dependent Mean 40027 Adj R-Sq 0.9514
Coeff Var 2.18079
Parameter
Estimates
Parameter Standard Standardized
Variable DF
Estimate Error t Value Pr > |t| Estimate
Intercept 1
879.92881 1290.86015 0.68
0.4963 0
tcoyrs 1
2873.73397 58.67805 48.97
<.0001 0.76823
SAT 1
16.78944 0.58329 28.78
<.0001 0.45131
evaluation 1 167.60113 7.41895
22.59 <.0001 0.35533
hsGPA 1
23.60276 190.67325 0.12
0.9016 0.00349
cGPA 1
-300.58660 425.75885 -0.71
0.4810 -0.01992
Parameter
Estimates
Squared Squared
Semi-partial Partial
Variable DF Corr Type I Corr Type I
Intercept 1 . .
tcoyrs 1
0.61628 0.61628
SAT 1 0.20936 0.54559
evaluation 1 0.12672 0.72674
hsGPA 1
0.00017031 0.00357
cGPA 1
0.00012230 0.00258
Chrissy Regression by All Variables 17
The REG Procedure
Model: MODEL1
Dependent Variable: income
Output
Statistics
Dep Var Predicted Std Error Std Error Student
Obs income Value Mean Predict Residual
Residual
Residual
1 48640
49098 188.9551 -457.5219 852.2
-0.537
2 40624
39728 118.1052 896.3163
864.9 1.036
3 34898
35037 178.3221 -138.8227 854.5
-0.162
4 39069
38513 168.7891 555.9317
856.4 0.649
5 36800
38341 87.2795 -1541
868.5 -1.775
6 43389
43623 127.8249 -233.8714 863.5
-0.271
7 43423
43079 81.0293 344.0043
869.1 0.396
8 38594
38070 163.3155 524.3896
857.5 0.612
9 37549
38751 143.4823 -1202
861.0 -1.396
10 39564
39682 106.4288 -118.0749 866.4
-0.136
11 42738
43575 156.9844 -836.8638 858.7
-0.975
12 36049
35162 223.7367 887.1182
843.7 1.051
13 34933
35426 150.9725 -492.7696 859.7
-0.573
14 38913
39505 109.7891 -591.5241 866.0
-0.683
15 36021
35804 181.6489 216.5434
853.8 0.254
16 41591
40422 174.4962 1169
855.3 1.367
17 34726
35377 140.9060 -651.3481 861.4
-0.756
18 38861
39594 139.0805 -732.6667 861.7
-0.850
19 28477
29742 209.6945 -1265
847.3 -1.492
20 38804
38800 179.7016 4.1417
854.2 0.00485
21 40013
38499 169.7683 1514
856.2 1.768
22 36933
37284 129.5356 -351.1068 863.2
-0.407
23 40201
39439 243.5114 762.3706
838.2 0.909
24 37044
37653 176.0120 -608.6065 855.0
-0.712
25 31470
30803 210.5962 666.7388
847.1 0.787
26 44923
44979 181.9478 -56.4863
853.7 -0.0662
27 43957
44351 170.7211 -393.9674 856.0
-0.460
28 36681
34458 150.2325 2223
859.9 2.586
29 39461
41285 126.2105 -1824
863.7 -2.112
30 46532
46206 211.8349 325.9019
846.8 0.385
31 42243
42011 141.7495 231.5098
861.3 0.269
32 38264
38220 143.4690 43.9505
861.0 0.0510
33 40234
41128 84.2708 -893.7816 868.8
-1.029
34 47567
46692 187.7482 874.7747
852.5 1.026
35 38956
40014 127.6820 -1058
863.5 -1.225
36 42061
41593 95.8228 468.4010
867.6 0.540
37 43943
44493 123.5660 -550.3120 864.1
-0.637
38 35736
35684 154.0472 52.2690
859.2 0.0608
39 41491
41876 214.0001 -385.1238 846.3
-0.455
40 40821
40465 173.5338 355.5106
855.5 0.416
41 45078
43444 109.7824 1634
866.0 1.887
42 48144
46525 162.0149 1619
857.7 1.887
43 43792
43616 148.7776 176.4892
860.1 0.205
44 42696
41224 123.6463 1472
864.1 1.704
45 38037
37757 173.6855 280.4609
855.4 0.328
46 35978
36137 127.4298 -158.5849 863.5
-0.184
47 36366
37924 192.5447 -1558
851.4 -1.830
48 44142
43883 134.7110 258.5570
862.4 0.300
49 34816
35270 245.8759 -453.9635 837.6
-0.542
50 39879
40849 232.7477 -969.5969 841.3
-1.153
51 36287
34924 162.3653 1363
857.7 1.590
52 46177
45310 170.8456 867.1527
856.0 1.013
53 35214
35102 137.4032 111.8547
862.0 0.130
54 28198
28774 208.8413 -575.7831 847.5
-0.679
55 31356
33279 183.4826 -1923
853.4 -2.253
56 35622
36266 112.9222 -643.6319 865.6
-0.744
57 41313
42420 110.7047 -1107
865.8 -1.278
58 36101
36308 103.5135 -206.7782 866.7
-0.239
59 37343
38287 88.1244 -944.0362 868.4
-1.087
60 39032
39455 74.2108 -423.0596 869.7
-0.486
61 48542
47603 160.0549 938.5725
858.1 1.094
62 36906
36817 160.4609 89.2854
858.0 0.104
63
40445 40721 67.2777 -276.1467 870.3
-0.317
64 39434
39829 117.0389 -395.2256 865.0
-0.457
65 39208
40296 165.2076 -1088
857.1 -1.269
Chrissy Regression by All Variables 18
The REG Procedure
Model: MODEL1
Dependent Variable: income
Output Statistics
Cook's
Obs
-2-1 0 1 2 D
1 | *|
| 0.002
2 | |**
| 0.003
3 | |
| 0.000
4 | |*
| 0.003
5 | ***|
| 0.005
6 |
| | 0.000
7 | |
| 0.000
8 | |*
| 0.002
9 | **|
| 0.009
10 | |
| 0.000
11 | *|
| 0.005
12 | |**
| 0.013
13 | *|
| 0.002
14 | *|
| 0.001
15 | |
| 0.000
16 | |**
| 0.013
17 | *|
| 0.003
18 | *|
| 0.003
19 |
**| | 0.023
20 | |
| 0.000
21 | |***
| 0.020
22 | |
| 0.001
23 | |*
| 0.012
24 | *|
| 0.004
25 | |*
| 0.006
26 | |
| 0.000
27 | |
| 0.001
28 | |***** | 0.034
29 | ****|
| 0.016
30 | |
| 0.002
31 | |
| 0.000
32 |
| | 0.000
33 | **|
| 0.002
34 | |**
| 0.009
35 | **|
| 0.005
36 | |*
| 0.001
37 | *|
| 0.001
38 | |
| 0.000
39 | |
| 0.002
40 | |
| 0.001
41 | |***
| 0.010
42 | |***
| 0.021
43 | |
| 0.000
44 | |***
| 0.010
45 |
| | 0.001
46 | |
| 0.000
47 | ***|
| 0.029
48 | |
| 0.000
49 | *|
| 0.004
50 | **|
| 0.017
51 | |***
| 0.015
52 | |**
| 0.007
53 | |
| 0.000
54 | *|
| 0.005
55 | ****|
| 0.039
56 | *|
| 0.002
57 | **|
| 0.004
58 |
| | 0.000
59 | **|
| 0.002
60 | |
| 0.000
61 | |**
| 0.007
62 | |
| 0.000
63 | |
| 0.000
64 | |
| 0.001
65 | **|
| 0.010
Chrissy Regression by All Variables 19
The REG Procedure
Model: MODEL1
Dependent Variable: income
Output Statistics
Dep Var Predicted Std Error Std Error Student
Obs income Value Mean Predict Residual
Residual
Residual
66 41522
40944 136.2478 578.0647
862.2 0.670
67 40124
39383 117.3004 740.8781
865.0 0.857
68 42416
41597 132.1061 819.0660
862.8 0.949
69 30772
30057 213.4224 714.6657
846.4 0.844
70 42868
41843 110.7572 1025
865.8 1.184
71 42662
42293 163.7175 369.4459
857.4 0.431
72 41525
41232 194.1622 293.1281
851.0 0.344
73
42154 42719 85.4916 -565.4200 868.7
-0.651
74 39215
40959 110.3095 -1744
865.9 -2.014
75 45773
46761 147.6845 -987.7227 860.3
-1.148
76 43388
43023 207.6988
364.9399 847.8 0.430
77 40282
40193 106.1039 88.7790
866.4 0.102
78 44462
44652 116.5332 -190.2808 865.1
-0.220
79 33693
32884 157.5263 808.5887
858.6 0.942
80 38791
39669 137.0216 -878.2590 862.1
-1.019
81 44734
44486 120.8042 247.7062
864.5 0.287
82 42003
42693 117.2935 -690.2272 865.0
-0.798
83 44269
43650 108.9122 618.5314
866.1 0.714
84 42236
41580 100.7781 656.0043
867.1 0.757
85 48139
47624 152.5206 514.7776
859.5 0.599
86
45789 44859 147.4839
930.2533 860.3 1.081
87 37160
37321 146.8085 -160.8154 860.5
-0.187
88 45106
45902 142.1790 -796.3752 861.2
-0.925
89 39023
38537 173.7740 486.2740
855.4 0.568
90 37390
37747 121.5474 -357.3538 864.4
-0.413
91 46177
45233 152.4871 944.0031
859.5 1.098
92 41086
40935 79.1841 150.5962
869.3 0.173
93 43262
42914 165.9229 348.4758
857.0 0.407
94 38619
40036 88.7461 -1417
868.4 -1.632
95 37428
36677 150.5317 750.5105
859.8 0.873
96 47050
46192 142.9433 857.5538
861.1 0.996
97 41497
41167 124.9438 329.8782
863.9 0.382
98 38878
39520 174.9834 -642.1362 855.2
-0.751
99 46391
45940 161.5652 450.9194
857.8 0.526
100 40754
40454 122.0788 300.2686
864.3 0.347
101 37417
38078 150.2808 -660.8998 859.9
-0.769
102 40191
40896 82.0665 -705.0453 869.0
-0.811
103 36183
36566 133.1108 -383.0445 862.7
-0.444
104 42131
42492 175.5188 -361.2699 855.1
-0.423
105 43130
43261 103.9621 -131.4303 866.7
-0.152
106 42167
41763 200.9943 404.4978
849.4 0.476
107 41733
41444 128.1154 288.8209
863.4 0.334
108 40179
41423 168.4572 -1244
856.5 -1.452
109 40062
40857 131.7252 -794.5619 862.9
-0.921
110 47664
48677 199.8181 -1013
849.7 -1.192
111 40127
40446 105.5963 -319.0505 866.5
-0.368
112 41683
42565 131.8399 -882.1064 862.9
-1.022
113 33181
34613 141.7959 -1432
861.3 -1.663
114 43244
43851 151.3756 -606.7530 859.7
-0.706
115 32370
32645 163.2220 -274.9144 857.5
-0.321
116 44515
45803 152.2278 -1288
859.5 -1.498
117 34931
34843 116.9804 87.6981
865.0 0.101
118 40011
40246 118.2762 -234.5005 864.8
-0.271
119 45250
45283 125.3847 -32.7125
863.8 -0.0379
120 41903
42883 144.7985 -980.0128 860.8
-1.138
121 38320
37979 81.1165 340.6512
869.1 0.392
122 42932
42928 107.1749 4.4243
866.3 0.00511
123 37456
37424 158.6468 31.7921
858.4 0.0370
124 43057
41981 101.1043 1076
867.0 1.241
125 41194
39974 180.2391 1220
854.1 1.429
126 37850
36458 120.0247 1392
864.6 1.610
127 38961
36995 189.0433 1966
852.2 2.307
128 41686
42234 123.6522 -548.0433 864.1
-0.634
129 39894
40965 124.2744 -1071
864.0 -1.240
130 42017
43192 131.8778 -1175
862.9 -1.361
Chrissy Regression by All Variables 20
The REG Procedure
Model: MODEL1
Dependent Variable: income
Output Statistics
Cook's
Obs
-2-1 0 1 2 D
66 | |*
| 0.002
67 | |*
| 0.002
68 | |*
| 0.004
69 | |*
| 0.008
70 | |**
| 0.004
71 |
| | 0.001
72 | |
| 0.001
73 | *|
| 0.001
74 | ****|
| 0.011
75 | **| |
0.006
76 | |
| 0.002
77 | |
| 0.000
78 | |
| 0.000
79 | |*
| 0.005
80 | **|
| 0.004
81 | |
| 0.000
82 | *|
| 0.002
83 | |*
| 0.001
84 |
|* | 0.001
85 | |*
| 0.002
86 | |**
| 0.006
87 | |
| 0.000
88 | *| |
0.004
89 | |*
| 0.002
90 | |
| 0.001
91 | |**
| 0.006
92 | |
| 0.000
93 |
| | 0.001
94 | ***|
| 0.005
95 | |*
| 0.004
96 | |*
| 0.005
97 |
| | 0.001
98 | *|
| 0.004
99 | |*
| 0.002
100 | |
| 0.000
101 | *|
| 0.003
102 | *|
| 0.001
103 | |
| 0.001
104 | |
| 0.001
105 | |
| 0.000
106 |
| | 0.002
107 | |
| 0.000
108 | **|
| 0.014
109 | *|
| 0.003
110 |
**| | 0.013
111 | |
| 0.000
112 | **|
| 0.004
113 | ***|
| 0.012
114 | *|
| 0.003
115 | |
| 0.001
116 | **|
| 0.012
117 | |
| 0.000
118 | |
| 0.000
119 |
| | 0.000
120 | **|
| 0.006
121 | |
| 0.000
122 | |
| 0.000
123 |
| | 0.000
124 | |**
| 0.003
125 | |**
| 0.015
126 | |***
| 0.008
127 | |**** |
0.044
128 | *|
| 0.001
129 | **|
| 0.005
130 | **|
| 0.007
Chrissy Regression by All Variables 21
The REG Procedure
Model: MODEL1
Dependent Variable: income
Output Statistics
Dep Var Predicted Std Error Std Error Student
Obs income Value Mean Predict Residual
Residual
Residual
131 43604
43016 165.1556 587.6309
857.1 0.686
132 41151
42003 96.8359 -852.0638 867.5
-0.982
133 42929
41303 116.9996 1626
865.0 1.880
134 39742
39820 108.2539 -77.9808
866.2 -0.0900
135 38811
39077 127.1147 -265.9704 863.6
-0.308
136 42379
43154 101.0365 -774.9518 867.0
-0.894
137 37305
36536 175.8181 769.0040
855.0 0.899
138 36304
36358 136.5098 -54.3145
862.2 -0.0630
139 41014
40384 178.1786 630.2153
854.5 0.738
140 34858
33906 135.8946 951.5727
862.3 1.104
141 40557
40569 182.8451 -11.5371
853.5 -0.0135
142 41138
42337 142.0000 -1199
861.3 -1.392
143 30330
31078 203.8598 -747.9080 848.8
-0.881
144 35994
35563 210.2519 431.2279
847.2 0.509
145 34642
33055 146.0697 1587
860.6 1.844
146 37012
37227 168.7146 -215.2468 856.4
-0.251
147 42258
42502 86.7878 -244.1593 868.6
-0.281
148 34077
33303 134.3932 773.7295
862.5 0.897
149 35649
36365 150.6881 -715.7745 859.8
-0.832
150 41145
41657 117.8798 -512.1082 864.9
-0.592
151 33188
33062 173.8817 126.2672
855.4 0.148
152 37999
38425 104.7494 -425.5792 866.6
-0.491
153 34255
34924 208.6729 -668.8675 847.6
-0.789
154 35193
35896 149.1187 -702.5086 860.1
-0.817
155 38148
39378 92.7941 -1230
868.0 -1.417
156 38384
38235 114.2305 148.7258
865.4 0.172
157 42202
41459 102.2766 743.2083
866.9 0.857
158 40867
40993 142.1885 -126.4153 861.2
-0.147
159 42918
41384 132.2229 1534
862.8 1.778
160 39402
38796 107.0470 606.4552
866.3 0.700
161 42609
41452 136.3724 1157
862.2 1.342
162 37356
37820 150.1555 -463.9220 859.9
-0.540
163 40276
39703 129.9258 572.8147
863.2 0.664
164
41032 42320 195.1636 -1288
850.8 -1.513
165 38647
37945 152.2914 701.5829
859.5 0.816
166 42340
40572 110.6399 1768
865.9 2.042
167 43785
42133 134.9560 1652
862.4 1.916
168 41218
41093 198.4618 125.1568
850.0 0.147
169 47834
47360 208.5058 474.2230
847.6 0.559
170 34350
33784 143.9983 565.5655
860.9 0.657
171 37293
36577 168.6554 716.3241
856.4 0.836
172 37461
36894 121.8438 566.6226
864.4 0.656
173 51341
51212 230.1445 129.3699
842.0 0.154
174 36055
37365 161.0505 -1310
857.9 -1.527
175 35499
37021 147.0127 -1522
860.4 -1.769
176 40852
41718 97.7103 -866.2486 867.4
-0.999
177 44598
44011 97.2596 586.9065
867.5 0.677
178 45455
45636 229.5611 -180.5328 842.2
-0.214
179 34753
35946 167.8522 -1193
856.6 -1.393
180 38512
39515 191.9731 -1003
851.5 -1.178
181 35697
35206 162.9420 491.3065
857.6 0.573
182 44784
42658 149.7505 2126
860.0 2.473
183 42151
41825 112.5479 325.9163
865.6 0.377
184 41244
40257 169.8355 987.2283
856.2 1.153
185 41451
41231 127.4946 220.4565
863.5 0.255
186 44168
43384 110.6869 783.8595 865.9
0.905
187 37125
38247 149.1875 -1122
860.1 -1.305
188 38917
37986 108.1077 931.1370
866.2 1.075
189 44552
44755 116.8989 -203.3436 865.0
-0.235
190 40673
41885 153.9707 -1212
859.2 -1.411
191 40842
41198 111.4712 -356.0633 865.7
-0.411
192 39442
37781 144.3569 1661
860.9 1.929
193 39445
38571 190.8834 873.7374
851.8 1.026
194 41298
41365 141.6986 -66.5275
861.3 -0.0772
195 37725
38077 237.8265 -351.6302 839.9
-0.419
Chrissy Regression by All Variables 22
The REG Procedure
Model: MODEL1
Dependent Variable: income
Output Statistics
Cook's
Obs
-2-1 0 1 2 D
131 | |*
| 0.003
132 |
*| | 0.002
133 | |***
| 0.011
134 | |
| 0.000
135 | |
| 0.000
136 |
*| | 0.002
137 | |*
| 0.006
138 | |
| 0.000
139 | |*
| 0.004
140 | |**
| 0.005
141 | |
| 0.000
142 | **|
| 0.009
143 | *|
| 0.007
144 | |*
| 0.003
145 |
|*** | 0.016
146 | |
| 0.000
147 | |
| 0.000
148 | |*
| 0.003
149 | *|
| 0.004
150 | *|
| 0.001
151 | |
| 0.000
152 | |
| 0.001
153 | *|
| 0.006
154 | *|
| 0.003
155 | **|
| 0.004
156 | |
| 0.000
157 | |*
| 0.002
158 |
| | 0.000
159 | |***
| 0.012
160 | |*
| 0.001
161 | |**
| 0.008
162 | *|
| 0.001
163 | |*
| 0.002
164 | ***|
| 0.020
165 | |*
| 0.003
166 | |****
| 0.011
167 | |***
| 0.015
168 | |
| 0.000
169 | |*
| 0.003
170 | |*
| 0.002
171 |
|* | 0.005
172 | |*
| 0.001
173 | |
| 0.000
174 | ***|
| 0.014
175 | ***|
| 0.015
176 | *|
| 0.002
177 | |*
| 0.001
178 | |
| 0.001
179 | **|
| 0.012
180 | **|
| 0.012
181 | |*
| 0.002
182 | |****
| 0.031
183 | |
| 0.000
184 |
|** | 0.009
185 | |
| 0.000
186 | |*
| 0.002
187 | **|
| 0.009
188 | |**
| 0.003
189 | |
| 0.000
190 | **|
| 0.011
191 | |
| 0.000
192 | |***
| 0.017
193 | |**
| 0.009
194 | |
| 0.000
195 | |
| 0.002
Chrissy Regression by All Variables 23
The REG Procedure
Model: MODEL1
Dependent Variable: income
Output Statistics
Dep Var Predicted Std Error Std Error Student
Obs income Value Mean Predict Residual
Residual
Residual
196 37356
36834 173.7102 522.4019
855.4 0.611
197 41817
43003 142.8060 -1186
861.1 -1.377
198 39697
38801 219.6641 896.2012
844.8 1.061
199 41826
43485 211.5881 -1659
846.9 -1.959
Output Statistics
Cook's
Obs
-2-1 0 1 2 D
196 | |*
| 0.003
197 |
**| | 0.009
198 | |**
| 0.013
199 | ***|
| 0.040
Sum of Residuals 0
Sum of Squared Residuals
147056079
Predicted Residual SS (PRESS) 156412298
