Nama Npm Kelas Matakuliah : Krysda Marsina Situmorang : 174210027 : Agribisnis 6/D : Ekonometrika 1. Lakukanlah uji asumsi klasik dengan menggunakan uji multikolinearitas, autokorelasi, heteroskedastisitas dan normalitas dengan menggunakan sampel n=35. Jawab : No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 Berat badan (kg) 75 80 87 65 67 78 79 82 84 77 66 76 74 83 68 70 76 90 89 86 88 91 92 88 80 66 67 68 80 86 87 90 Tinggi badan (cm) 150 160 155 164 150 155 170 164 167 150 170 180 177 175 145 166 158 160 155 157 155 175 157 160 160 160 146 148 157 158 159 165 33 34 35 94 95 89 166 167 170 A. Uji Multikolinearitas Variables Entered/Removeda Variables Variables Model Entered Removed Method 1 tinggi badanb . Enter a. Dependent Variable: berat badan b. All requested variables entered. Model Summary Adjusted R Std. Error of Model R R Square Square the Estimate a 1 .239 .057 .029 8.976 a. Predictors: (Constant), tinggi badan ANOVAa Sum of Model Squares df Mean Square 1 Regression 161.292 1 161.292 Residual 2658.879 33 80.572 Total 2820.171 34 a. Dependent Variable: berat badan b. Predictors: (Constant), tinggi badan Unstandardized Coefficients Model 1 (Constant) F 2.002 Sig. .166b Coefficientsa Standardized Coefficients B Std. Error 40.601 28.150 Beta t 1.442 Sig. .159 Collinearity Statistics Toleranc e VIF tinggi .247 badan a. Dependent Variable: berat badan .175 .239 1.415 .166 1.000 Coefficient Correlationsa Model 1 Correlations tinggi badan tinggi badan 1.000 Covariances tinggi badan a. Dependent Variable: berat badan .031 Collinearity Diagnosticsa Model Dimension Eigenvalue 1 1 1.999 2 .001 Variance Proportions Condition tinggi Index (Constant) badan 1.000 .00 .00 37.079 1.00 1.00 a. Dependent Variable: berat badan B. Uji Autokorelasi Variables Entered/Removeda Variables Variables Model Entered Removed Method b 1 tinggi badan . Enter a. Dependent Variable: berat badan b. All requested variables entered. Model Summaryb Adjusted R Std. Error of Model R R Square Square the Estimate a 1 .239 .057 .029 8.976 a. Predictors: (Constant), tinggi badan b. Dependent Variable: berat badan DurbinWatson .784 K=2, n=35 maka dL=1.353 dan dU=1.584 Karena nilai DW lebih kecil dari du dan lebih kecil dari nilai dl, maka tidak menghasilkan kesimpulan yang tidak pasti 1.000 ANOVAa Sum of Model Squares df Mean Square 1 Regression 161.292 1 161.292 Residual 2658.879 33 80.572 Total 2820.171 34 a. Dependent Variable: berat badan b. Predictors: (Constant), tinggi badan Unstandardized Coefficients F 2.002 Coefficientsa Standardized Coefficients Model B Std. Error 1 (Constant) 40.601 28.150 tinggi .247 .175 badan a. Dependent Variable: berat badan Beta .239 t 1.442 Sig. .159 1.415 .166 Coefficient Correlationsa Model 1 Correlations tinggi badan Covariances tinggi badan a. Dependent Variable: berat badan tinggi badan 1.000 .031 Collinearity Diagnosticsa Variance Proportions Model Dimension Eigenvalue 1 1 1.999 2 .001 a. Dependent Variable: berat badan Sig. .166b Condition Index (Constant) 1.000 .00 37.079 1.00 tinggi badan .00 1.00 Collinearity Statistics Toleranc e VIF 1.000 1.000 Predicted Value Residual Std. Predicted Value Std. Residual Residuals Statisticsa Minimu Maximu m m Mean 76.44 85.10 80.37 -16.624 13.117 .000 Std. Deviation 2.178 8.843 N 35 35 -1.803 2.169 .000 1.000 35 -1.852 1.461 .000 .985 35 a. Dependent Variable: berat badan C. Uji Heteroskedastisitas Variables Entered/Removeda Variables Variables Model Entered Removed Method b 1 tinggi badan . Enter a. Dependent Variable: berat badan b. All requested variables entered. Model Summaryb Adjusted R Std. Error of Model R R Square Square the Estimate 1 .239a .057 .029 8.976 a. Predictors: (Constant), tinggi badan b. Dependent Variable: berat badan ANOVAa Sum of Model Squares df Mean Square 1 Regression 161.292 1 161.292 Residual 2658.879 33 80.572 Total 2820.171 34 a. Dependent Variable: berat badan b. Predictors: (Constant), tinggi badan F 2.002 Sig. .166b Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta 1 (Constant) 40.601 28.150 tinggi badan .247 .175 .239 a. Dependent Variable: berat badan t 1.442 1.415 Sig. .159 .166 Residuals Statisticsa Minimu Maximu m m Mean 76.44 85.10 80.37 -16.624 13.117 .000 Std. Deviation 2.178 8.843 .000 1.000 35 .000 .985 35 Predicted Value Residual Std. Predicted -1.803 2.169 Value Std. Residual -1.852 1.461 a. Dependent Variable: berat badan N 35 35 • Terjadi heteroskedastisitas karena titik-titik tidak menyebar secara acak serta tidak tersebar baik di atas maupun di bawah angka 0 pada sumbu Y. D. Uji Normalitas Variables Entered/Removeda Variables Variables Model Entered Removed Method 1 tinggi badanb . Enter a. Dependent Variable: berat badan b. All requested variables entered. Model 1 R .239a Model Summaryb Adjusted R Std. Error of R Square Square the Estimate .057 .029 8.976 a. Predictors: (Constant), tinggi badan b. Dependent Variable: berat badan ANOVAa Sum of Model Squares df Mean Square 1 Regression 161.292 1 161.292 Residual 2658.879 33 80.572 Total 2820.171 34 a. Dependent Variable: berat badan b. Predictors: (Constant), tinggi badan F 2.002 Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta 1 (Constant) 40.601 28.150 tinggi badan .247 .175 .239 a. Dependent Variable: berat badan Sig. .166b t 1.442 1.415 Sig. .159 .166 Residuals Statisticsa Minimu Maximu m m Mean 76.44 85.10 80.37 -16.624 13.117 .000 Std. Deviation 2.178 8.843 .000 1.000 35 .000 .985 35 Predicted Value Residual Std. Predicted -1.803 2.169 Value Std. Residual -1.852 1.461 a. Dependent Variable: berat badan N 35 35 Normal, karena grafik histogram memberikan pola distribusi yang tidak merata (kurtosis positif). Normal karena titik-titik menyebar di sekitar garis diagonal, serta penyebarannya mengikuti arah garis diagonal.