General Linear Models
Analysis of Variance for WysoscCm
-----------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 474,137 4 118,534 9,39 0,0041
Kombinacja 20,0893 2 10,0447 0,80 0,4839
Residual 100,951 8 12,6188
------------------------------------------------------------------------------------
Analysis of Variance for SumaDlugPedow
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 102679,0 4 25669,7 9,12 0,0045
Kombinacja 1600,36 2 800,178 0,28 0,7597
Residual 22506,1 8 2813,26
------------------------------------------------------------------------------------
Total (corrected) 126785,0 14
Analysis of Variance for SreDlugPedu
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 312,149 4 78,0373 9,02 0,0046
Kombinacja 13,584 2 6,792 0,79 0,4882
Residual 69,1827 8 8,64783
------------------------------------------------------------------------------------
Total (corrected) 394,916 14
Analysis of Variance for SrednicaMm
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 40,2827 4 10,0707 21,42 0,0002
Kombinacja 0,185333 2 0,0926667 0,20 0,8250
Residual 3,76133 8 0,470167
------------------------------------------------------------------------------------
Total (corrected) 44,2293 14
Analysis of Variance for PpppMm2
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 22946,7 4 5736,67 20,55 0,0003
Kombinacja 209,231 2 104,615 0,37 0,6990
Residual 2233,71 8 279,213
------------------------------------------------------------------------------------
Total (corrected) 25389,6 14
General Linear Models
General Linear Models
---------------------
Number of dependent variables: 5
Number of categorical factors: 2
Number of quantitative factors: 0
Analysis of Variance for WysoscCm
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 494,227 6 82,3711 6,53 0,0093
Residual 100,951 8 12,6188
-----------------------------------------------------------------------------
Total (Corr.) 595,177 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 474,137 4 118,534 9,39 0,0041
Kombinacja 20,0893 2 10,0447 0,80 0,4839
Residual 100,951 8 12,6188
------------------------------------------------------------------------------------
Total (corrected) 595,177 14
All F-ratios are based on the residual mean square error.
R-Squared = 83,0386 percent
R-Squared (adjusted for d.f.) = 70,3175 percent
Standard Error of Est. = 3,5523
Mean absolute error = 2,112
Durbin-Watson statistic = 2,6919
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 12,6188
MAE 2,112
MAPE 1,24536
ME -2,27374E-14
MPE -0,0228615
Analysis of Variance for SumaDlugPedow
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 104279,0 6 17379,9 6,18 0,0110
Residual 22506,1 8 2813,26
-----------------------------------------------------------------------------
Total (Corr.) 126785,0 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 102679,0 4 25669,7 9,12 0,0045
Kombinacja 1600,36 2 800,178 0,28 0,7597
Residual 22506,1 8 2813,26
------------------------------------------------------------------------------------
Total (corrected) 126785,0 14
All F-ratios are based on the residual mean square error.
R-Squared = 82,2487 percent
R-Squared (adjusted for d.f.) = 68,9352 percent
Standard Error of Est. = 53,0401
Mean absolute error = 32,1413
Durbin-Watson statistic = 2,44676
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 2813,26
MAE 32,1413
MAPE 10,4841
ME 3,22113E-14
MPE -1,37755
Analysis of Variance for SreDlugPedu
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 325,733 6 54,2889 6,28 0,0105
Residual 69,1827 8 8,64783
-----------------------------------------------------------------------------
Total (Corr.) 394,916 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 312,149 4 78,0373 9,02 0,0046
Kombinacja 13,584 2 6,792 0,79 0,4882
Residual 69,1827 8 8,64783
------------------------------------------------------------------------------------
Total (corrected) 394,916 14
All F-ratios are based on the residual mean square error.
R-Squared = 82,4817 percent
R-Squared (adjusted for d.f.) = 69,3429 percent
Standard Error of Est. = 2,94072
Mean absolute error = 1,79289
Durbin-Watson statistic = 2,51705
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 8,64783
MAE 1,79289
MAPE 6,56986
ME -4,73695E-15
MPE -0,570467
Analysis of Variance for SrednicaMm
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 40,468 6 6,74467 14,35 0,0007
Residual 3,76133 8 0,470167
-----------------------------------------------------------------------------
Total (Corr.) 44,2293 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 40,2827 4 10,0707 21,42 0,0002
Kombinacja 0,185333 2 0,0926667 0,20 0,8250
Residual 3,76133 8 0,470167
------------------------------------------------------------------------------------
Total (corrected) 44,2293 14
All F-ratios are based on the residual mean square error.
R-Squared = 91,4958 percent
R-Squared (adjusted for d.f.) = 85,1177 percent
Standard Error of Est. = 0,685687
Mean absolute error = 0,416
Durbin-Watson statistic = 2,53669
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 0,470167
MAE 0,416
MAPE 2,83788
ME 1,65793E-15
MPE -0,111688
Analysis of Variance for PpppMm2
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 23155,9 6 3859,32 13,82 0,0008
Residual 2233,71 8 279,213
-----------------------------------------------------------------------------
Total (Corr.) 25389,6 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 22946,7 4 5736,67 20,55 0,0003
Kombinacja 209,231 2 104,615 0,37 0,6990
Residual 2233,71 8 279,213
------------------------------------------------------------------------------------
Total (corrected) 25389,6 14
All F-ratios are based on the residual mean square error.
R-Squared = 91,2023 percent
R-Squared (adjusted for d.f.) = 84,604 percent
Standard Error of Est. = 16,7097
Mean absolute error = 10,1108
Durbin-Watson statistic = 2,52539
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 279,213
MAE 10,1108
MAPE 6,02317
ME 1,42109E-14
MPE -0,459018
The StatAdvisor
---------------
This pane summarizes the results of fitting 5 general linear
statistical model relating 5 dependent variables to 2 predictive
factors. Since the P-value in the first ANOVA table for WysoscCm is
less than 0.01, there is a statistically significant relationship
between WysoscCm and the predictor variables at the 99% confidence
level.
The R-Squared statistic indicates that the model as fitted explains
91,2023% of the variability in WysoscCm. The adjusted R-squared
statistic, which is more suitable for comparing models with different
numbers of independent variables, is 84,604%. The standard error of
the estimate shows the standard deviation of the residuals to be
16,7097. This value can be used to construct prediction limits for
new observations by selecting the Reports option from the text menu.
The mean absolute error (MAE) of 2,112 is the average value of the
residuals. The Durbin-Watson (DW) statistic tests the residuals to
determine if there is any significant correlation based on the order
in which they occur in your data file. Since the DW value is greater
than 1.4, there is probably not any serious autocorrelation in the
residuals.
The output also summarizes the performance of the model in fitting
the data, and in predicting any values withheld from the fitting
process. It displays:
(1) the mean squared error (MSE)
(2) the mean absolute error (MAE)
(3) the mean absolute percentage error (MAPE)
(4) the mean error (ME)
(5) the mean percentage error (MPE)
Each of the statistics is based on the residuals. The first three
statistics measure the magnitude of the errors. A better model will
give a smaller value. The last two statistics measure bias. A better
model will give a value close to 0.0.
Multiple Comparisons for WysoscCm by Kombinacja
--------------------------------------------------------------------------------
Method: 95,0 percent Student-Newman-Keuls
Kombinacja Count LS Mean Homogeneous Groups
--------------------------------------------------------------------------------
2 5 165,62 X
1 5 166,78 X
3 5 168,44 X
--------------------------------------------------------------------------------
General Linear Models
General Linear Models
---------------------
Number of dependent variables: 5
Number of categorical factors: 2
Number of quantitative factors: 0
Analysis of Variance for WysoscCm
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 494,227 6 82,3711 6,53 0,0093
Residual 100,951 8 12,6188
-----------------------------------------------------------------------------
Total (Corr.) 595,177 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 474,137 4 118,534 9,39 0,0041
Kombinacja 20,0893 2 10,0447 0,80 0,4839
Residual 100,951 8 12,6188
------------------------------------------------------------------------------------
Total (corrected) 595,177 14
All F-ratios are based on the residual mean square error.
R-Squared = 83,0386 percent
R-Squared (adjusted for d.f.) = 70,3175 percent
Standard Error of Est. = 3,5523
Mean absolute error = 2,112
Durbin-Watson statistic = 2,6919
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 12,6188
MAE 2,112
MAPE 1,24536
ME -2,27374E-14
MPE -0,0228615
Analysis of Variance for SumaDlugPedow
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 104279,0 6 17379,9 6,18 0,0110
Residual 22506,1 8 2813,26
-----------------------------------------------------------------------------
Total (Corr.) 126785,0 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 102679,0 4 25669,7 9,12 0,0045
Kombinacja 1600,36 2 800,178 0,28 0,7597
Residual 22506,1 8 2813,26
------------------------------------------------------------------------------------
Total (corrected) 126785,0 14
All F-ratios are based on the residual mean square error.
R-Squared = 82,2487 percent
R-Squared (adjusted for d.f.) = 68,9352 percent
Standard Error of Est. = 53,0401
Mean absolute error = 32,1413
Durbin-Watson statistic = 2,44676
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 2813,26
MAE 32,1413
MAPE 10,4841
ME 3,22113E-14
MPE -1,37755
Analysis of Variance for SreDlugPedu
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 325,733 6 54,2889 6,28 0,0105
Residual 69,1827 8 8,64783
-----------------------------------------------------------------------------
Total (Corr.) 394,916 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 312,149 4 78,0373 9,02 0,0046
Kombinacja 13,584 2 6,792 0,79 0,4882
Residual 69,1827 8 8,64783
------------------------------------------------------------------------------------
Total (corrected) 394,916 14
All F-ratios are based on the residual mean square error.
R-Squared = 82,4817 percent
R-Squared (adjusted for d.f.) = 69,3429 percent
Standard Error of Est. = 2,94072
Mean absolute error = 1,79289
Durbin-Watson statistic = 2,51705
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 8,64783
MAE 1,79289
MAPE 6,56986
ME -4,73695E-15
MPE -0,570467
Analysis of Variance for SrednicaMm
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 40,468 6 6,74467 14,35 0,0007
Residual 3,76133 8 0,470167
-----------------------------------------------------------------------------
Total (Corr.) 44,2293 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 40,2827 4 10,0707 21,42 0,0002
Kombinacja 0,185333 2 0,0926667 0,20 0,8250
Residual 3,76133 8 0,470167
------------------------------------------------------------------------------------
Total (corrected) 44,2293 14
All F-ratios are based on the residual mean square error.
R-Squared = 91,4958 percent
R-Squared (adjusted for d.f.) = 85,1177 percent
Standard Error of Est. = 0,685687
Mean absolute error = 0,416
Durbin-Watson statistic = 2,53669
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 0,470167
MAE 0,416
MAPE 2,83788
ME 1,65793E-15
MPE -0,111688
Analysis of Variance for PpppMm2
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 23155,9 6 3859,32 13,82 0,0008
Residual 2233,71 8 279,213
-----------------------------------------------------------------------------
Total (Corr.) 25389,6 14
Type III Sums of Squares
------------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
------------------------------------------------------------------------------------
Powtorzenie 22946,7 4 5736,67 20,55 0,0003
Kombinacja 209,231 2 104,615 0,37 0,6990
Residual 2233,71 8 279,213
------------------------------------------------------------------------------------
Total (corrected) 25389,6 14
All F-ratios are based on the residual mean square error.
R-Squared = 91,2023 percent
R-Squared (adjusted for d.f.) = 84,604 percent
Standard Error of Est. = 16,7097
Mean absolute error = 10,1108
Durbin-Watson statistic = 2,52539
Residual Analysis
---------------------------------
Estimation Validation
n 15
MSE 279,213
MAE 10,1108
MAPE 6,02317
ME 1,42109E-14
MPE -0,459018
The StatAdvisor
---------------
This pane summarizes the results of fitting 5 general linear
statistical model relating 5 dependent variables to 2 predictive
factors. Since the P-value in the first ANOVA table for SumaDlugPedow
is less than 0.05, there is a statistically significant relationship
between SumaDlugPedow and the predictor variables at the 95%
confidence level.
The R-Squared statistic indicates that the model as fitted explains
91,2023% of the variability in SumaDlugPedow. The adjusted R-squared
statistic, which is more suitable for comparing models with different
numbers of independent variables, is 84,604%. The standard error of
the estimate shows the standard deviation of the residuals to be
16,7097. This value can be used to construct prediction limits for
new observations by selecting the Reports option from the text menu.
The mean absolute error (MAE) of 32,1413 is the average value of the
residuals. The Durbin-Watson (DW) statistic tests the residuals to
determine if there is any significant correlation based on the order
in which they occur in your data file. Since the DW value is greater
than 1.4, there is probably not any serious autocorrelation in the
residuals.
The output also summarizes the performance of the model in fitting
the data, and in predicting any values withheld from the fitting
process. It displays:
(1) the mean squared error (MSE)
(2) the mean absolute error (MAE)
(3) the mean absolute percentage error (MAPE)
(4) the mean error (ME)
(5) the mean percentage error (MPE)
Each of the statistics is based on the residuals. The first three
statistics measure the magnitude of the errors. A better model will
give a smaller value. The last two statistics measure bias. A better
model will give a value close to 0.0.
Multiple Comparisons for SumaDlugPedow by Kombinacja
--------------------------------------------------------------------------------
Method: 95,0 percent Student-Newman-Keuls
Kombinacja Count LS Mean Homogeneous Groups
--------------------------------------------------------------------------------
3 5 309,52 X
2 5 311,56 X
1 5 332,38 X
--------------------------------------------------------------------------------