85 117 2,40739 2,50964 0,04327 -0,10225 -1,01 X 94 560 1,60369 1,79453 0,04286 -0,19085 -1,87 X
106 685 1,46538 1,70801 0,02502 -0,24263 -2,26R 120 159 2,05365 2,31048 0,03103 -0,25683 -2,42R
123 3569 1,40654 1,54085 0,05212 -0,13431 -1,38 X 128 925 1,46538 1,69457 0,06061 -0,22919 -2,48RX
132 1644 1,73838 1,99401 0,02543 -0,25563 -2,38R 139 162 1,90472 2,16956 0,02077 -0,26485 -2,44R
140 365 1,81757 2,07282 0,02090 -0,25525 -2,35R 141 342 1,76641 1,98976 0,01536 -0,22335 -2,04R
R denotes an observation with a large standardized residual. X denotes an observation whose X value gives it large leverage.
b. Persamaan Regresi Kedua
The regression equation is Ln Y = 1,79 - 0,000060 X1 - 0,000000 X2 + 0,0864 X3 - 0,0560 X4 -
0,00137 X5 Predictor Coef SE Coef T P
Constant 1,79086 0,07419 24,14 0,000 X1 -0,00006019 0,00001879 -3,20 0,002
X2 -0,00000000 0,00000000 -0,13 0,894
Lampiran 4. Lanjutan
X3 0,086441 0,006524 13,25 0,000 X4 -0,05596 0,02724 -2,05 0,042
X5 -0,001368 0,003904 -0,35 0,727 S = 0,110123 R-Sq = 68,7 R-Sqadj = 67,6
Analysis of Variance Source DF SS MS F P
Regression 5 3,80221 0,76044 62,71 0,000 Residual Error 143 1,73417 0,01213
Total 148 5,53638 Source DF Seq SS
X1 1 1,10976 X2 1 0,55360
X3 1 2,08762 X4 1 0,04974
X5 1 0,00149 Unusual Observations
Obs X1 Ln Y Fit SE Fit Residual St Resid 26 420 2,36847 1,99000 0,01829 0,37847 3,49R
44 291 2,38184 2,48160 0,03835 -0,09977 -0,97 X 85 117 2,40739 2,51207 0,04259 -0,10468 -1,03 X
106 685 1,46538 1,70649 0,02457 -0,24111 -2,25R 120 159 2,05365 2,31065 0,03093 -0,25700 -2,43R
123 3569 1,40654 1,54136 0,05194 -0,13482 -1,39 X 128 925 1,46538 1,69285 0,06023 -0,22747 -2,47RX
132 1644 1,73838 1,99376 0,02534 -0,25538 -2,38R 139 162 1,90472 2,16894 0,02064 -0,26423 -2,44R
140 365 1,81757 2,07149 0,02050 -0,25393 -2,35R 141 342 1,76641 1,99053 0,01516 -0,22412 -2,05R
Universitas Sumatera Utara
R denotes an observation with a large standardized residual. X denotes an observation whose X value gives it large leverage.
c. Persamaan Ketiga
The regression equation is Ln Y = 1,78 - 0,000060 X1 - 0,000000 X2 + 0,0865 X3 - 0,0545 X4
Predictor Coef SE Coef T P Constant 1,77552 0,05971 29,73 0,000
X1 -0,00006028 0,00001873 -3,22 0,002 X2 -0,00000000 0,00000000 -0,12 0,907
X3 0,086493 0,006503 13,30 0,000 X4 -0,05453 0,02685 -2,03 0,044
S = 0,109787 R-Sq = 68,6 R-Sqadj = 67,8 Analysis of Variance
Source DF SS MS F P Regression 4 3,80072 0,95018 78,83 0,000
Residual Error 144 1,73566 0,01205 Total 148 5,53638
Lampiran 4. Lanjutan
Source DF Seq SS X1 1 1,10976
X2 1 0,55360 X3 1 2,08762
X4 1 0,04974 Unusual Observations
Obs X1 Ln Y Fit SE Fit Residual St Resid 26 420 2,36847 1,98606 0,01440 0,38241 3,51R
44 291 2,38184 2,47708 0,03600 -0,09524 -0,92 X 74 996 1,90472 1,91504 0,03748 -0,01033 -0,10 X
85 117 2,40739 2,51754 0,03950 -0,11015 -1,08 X 106 685 1,46538 1,71058 0,02155 -0,24520 -2,28R
120 159 2,05365 2,31395 0,02938 -0,26030 -2,46R 123 3569 1,40654 1,53698 0,05025 -0,13044 -1,34 X
128 925 1,46538 1,68969 0,05937 -0,22431 -2,43RX 132 1644 1,73838 1,99809 0,02207 -0,25970 -2,41R
139 162 1,90472 2,17350 0,01597 -0,26879 -2,47R 140 365 1,81757 2,07582 0,01631 -0,25826 -2,38R
141 342 1,76641 1,99071 0,01510 -0,22429 -2,06R R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
d. Persamaan Regresi Keempat
