REGRESI DENGAN VARABEL FAKTOR/ KUALLTATIF - PowerPoint PPT Presentation
Title: REGRESI DENGAN VARABEL FAKTOR/ KUALLTATIF
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REGRESI DENGAN VARABEL FAKTOR/ KUALLTATIF
- KASUS I FAKTOR TIDAK BERPENGARUH
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(No Transcript)
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REGRESI DIPERIKSA INTERAKSI
- lm(formula y1 x1 g, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- (Intercept) 10.00000 1.23576 8.092 5.45e-11
- x1 3.00000 0.02475 121.230 lt 2e-16
- gT.P -0.65146 1.85766 -0.351 0.727
- x1gT.P 0.01779 0.03622 0.491 0.625
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 1.184 on 56 degrees of
freedom - Multiple R-squared 0.998, Adjusted R-squared
0.9979 - F-statistic 9476 on 3 and 56 DF, p-value lt
2.2e-16
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REGRESI DIPISAH
- lm(formula y1 g/x1 - 1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- gL 10.00000 1.23576 8.092 5.45e-11
- gP 9.34854 1.38701 6.740 9.30e-09
- gLx1 3.00000 0.02475 121.230 lt 2e-16
- gPx1 3.01779 0.02645 114.099 lt 2e-16
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 1.184 on 56 degrees of
freedom - Multiple R-squared 1, Adjusted R-squared
0.9999 - F-statistic 2.864e05 on 4 and 56 DF, p-value
lt 2.2e-16
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REGRESI DIGABUNG
- lm(formula y1 x1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- (Intercept) 9.60337 0.90543 10.61 3.35e-15
- x1 3.01053 0.01768 170.25 lt 2e-16
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 1.173 on 58 degrees of
freedom - Multiple R-squared 0.998, Adjusted R-squared
0.998 - F-statistic 2.899e04 on 1 and 58 DF, p-value
lt 2.2e-16
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FAKTOR BERPENGARUH TANPA INTERAKSI
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PERIKSA INTERAKSI
- lm(formula y2 x1 g, data DataSimReg)
- Coefficients
- Estimate Std. Error t value
Pr(gtt) - (Intercept) 52.38491 2.16798 24.163
lt2e-16 - x1 2.95164 0.04341 67.988
lt2e-16 - gT.P -102.82667 3.25903 -31.551
lt2e-16 - x1gT.P 0.05375 0.06354 0.846
0.401 - ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 2.078 on 56 degrees of
freedom - Multiple R-squared 0.9985, Adjusted R-squared
0.9985 - F-statistic 1.28e04 on 3 and 56 DF, p-value lt
2.2e-16
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PAKSA REGRESI BERBEDA
- lm(formula y2 g/x1 - 1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- gL 52.38491 2.16798 24.16 lt2e-16
- gP -50.44177 2.43334 -20.73 lt2e-16
- gLx1 2.95164 0.04341 67.99 lt2e-16
- gPx1 3.00539 0.04640 64.77 lt2e-16
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 2.078 on 56 degrees of
freedom - Multiple R-squared 0.9998, Adjusted R-squared
0.9998 - F-statistic 8.923e04 on 4 and 56 DF, p-value
lt 2.2e-16
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REGRESI PARALEL
- lm(formula y2 g x1 - 1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- gL 51.15128 1.60017 31.97 lt2e-16
- gP -48.95706 1.68119 -29.12 lt2e-16
- x1 2.97673 0.03162 94.13 lt2e-16
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 2.072 on 57 degrees of
freedom - Multiple R-squared 0.9998, Adjusted R-squared
0.9998 - F-statistic 1.196e05 on 3 and 57 DF, p-value
lt 2.2e-16
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REGRESI DIGABUNG
- lm(formula y2 x1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- (Intercept) 46.4770 38.8685 1.196 0.23666
- x1 2.0778 0.7591 2.737 0.00821
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 50.35 on 58 degrees of
freedom - Multiple R-squared 0.1144, Adjusted R-squared
0.09914 - F-statistic 7.493 on 1 and 58 DF, p-value
0.008211
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FAKTOR BERINTERAKSI
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MEMERIKSA INTERAKSI
- lm(formula y3 g x1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value
Pr(gtt) - (Intercept) 59.16291 2.08027 28.44
lt2e-16 - gT.P -125.53198 3.12719 -40.14
lt2e-16 - x1 -1.48226 0.04166 -35.58
lt2e-16 - gT.Px1 3.90656 0.06097 64.07
lt2e-16 - ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 1.994 on 56 degrees of
freedom - Multiple R-squared 0.9977, Adjusted R-squared
0.9976 - F-statistic 8101 on 3 and 56 DF, p-value lt
2.2e-16
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REGRESI DIPISAH
- lm(formula y3 g/x1 - 1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- gL 59.16291 2.08027 28.44 lt2e-16
- gP -66.36907 2.33490 -28.43 lt2e-16
- gLx1 -1.48226 0.04166 -35.58 lt2e-16
- gPx1 2.42430 0.04452 54.45 lt2e-16
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 1.994 on 56 degrees of
freedom - Multiple R-squared 0.9983, Adjusted R-squared
0.9981 - F-statistic 8028 on 4 and 56 DF, p-value lt
2.2e-16
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REGRESI PARALEL
- lm(formula y3 g x1 - 1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- gL -30.4926 13.1515 -2.319 0.02403
- gP 41.5335 13.8174 3.006 0.00393
- x1 0.3412 0.2599 1.313 0.19446
- ---
- Signif. codes 0 '' 0.001 '' 0.01 '' 0.05
'.' 0.1 ' ' 1 - Residual standard error 17.03 on 57 degrees of
freedom - Multiple R-squared 0.8707, Adjusted R-squared
0.8639 - F-statistic 127.9 on 3 and 57 DF, p-value lt
2.2e-16
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REGRESI DIGABUNG
- lm(formula y3 x1, data DataSimReg)
- Coefficients
- Estimate Std. Error t value Pr(gtt)
- (Intercept) -27.1295 30.8332 -0.880 0.383
- x1 0.9880 0.6022 1.641 0.106
- Residual standard error 39.94 on 58 degrees of
freedom - Multiple R-squared 0.04436, Adjusted R-squared
0.02788 - F-statistic 2.692 on 1 and 58 DF, p-value
0.1063
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