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