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Author*The author of this computation has been verified*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationFri, 04 Dec 2015 14:59:32 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/04/t1449242269598q122pjnhdgff.htm/, Retrieved Sat, 18 May 2024 09:04:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=285169, Retrieved Sat, 18 May 2024 09:04:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [Sport naar opleiding] [2015-12-04 14:59:32] [2b3692832aadae69996f201e477dca13] [Current]
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Dataseries X:
0,2782	'ja'	'A'
0,7218	'nee'	'A'
0,4392	'ja'	'B'
0,5608	'nee'	'B'
0,5436	'ja'	'C'
0,4564	'nee'	'C'
0,5857	'ja'	'D'
0,4143	'nee'	'D'
0,6441	'ja'	'E'
0,3559	'nee'	'E'
0,2937	'ja'	'A'
0,7063	'nee'	'A'
0,4960	'ja'	'B'
0,5040	'nee'	'B'
0,5244	'ja'	'C'
0,4756	'nee'	'C'
0,6679	'ja'	'D'
0,3321	'nee'	'D'
0,7155	'ja'	'E'
0,2845	'nee'	'E'
0,2914	'ja'	'A'
0,7086	'nee'	'A'
0,4297	'ja'	'B'
0,5703	'nee'	'B'
0,5283	'ja'	'C'
0,4717	'nee'	'C'
0,7114	'ja'	'D'
0,2886	'nee'	'D'
0,7011	'ja'	'E'
0,2989	'nee'	'E'
0,3616	'ja'	'A'
0,6384	'nee'	'A'
0,5298	'ja'	'B'
0,4702	'nee'	'B'
0,5749	'ja'	'C'
0,4251	'nee'	'C'
0,6564	'ja'	'D'
0,3436	'nee'	'D'
0,7721	'ja'	'E'
0,2279	'nee'	'E'
0,4182	'ja'	'A'
0,5818	'nee'	'A'
0,5754	'ja'	'B'
0,4246	'nee'	'B'
0,5943	'ja'	'C'
0,4057	'nee'	'C'
0,7292	'ja'	'D'
0,2708	'nee'	'D'
0,8000	'ja'	'E'
0,2000	'nee'	'E'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285169&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285169&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.3290.3430.1650.2240.3410.398-0.331-0.449-0.683-0.796

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 0.329 & 0.343 & 0.165 & 0.224 & 0.341 & 0.398 & -0.331 & -0.449 & -0.683 & -0.796 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285169&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]0.329[/C][C]0.343[/C][C]0.165[/C][C]0.224[/C][C]0.341[/C][C]0.398[/C][C]-0.331[/C][C]-0.449[/C][C]-0.683[/C][C]-0.796[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285169&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.3290.3430.1650.2240.3410.398-0.331-0.449-0.683-0.796







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A10.1480.14849.0160
Treatment_B10001
Treatment_A:Treatment_B10.9770.24480.6240
Residuals400.1210.003

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 0.148 & 0.148 & 49.016 & 0 \tabularnewline
Treatment_B & 1 & 0 & 0 & 0 & 1 \tabularnewline
Treatment_A:Treatment_B & 1 & 0.977 & 0.244 & 80.624 & 0 \tabularnewline
Residuals & 40 & 0.121 & 0.003 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285169&T=2

[TABLE]
[ROW][C]ANOVA Statistics[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]Sum Sq[/C][C]Mean Sq[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C][/C][C]1[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]1[/C][C]0.148[/C][C]0.148[/C][C]49.016[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]0[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]0.977[/C][C]0.244[/C][C]80.624[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]40[/C][C]0.121[/C][C]0.003[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285169&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285169&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A10.1480.14849.0160
Treatment_B10001
Treatment_A:Treatment_B10.9770.24480.6240
Residuals400.1210.003







Tukey Honest Significant Difference Comparisons
difflwruprp adj
nee-ja-0.109-0.14-0.0780
B-A0-0.070.071
C-A0-0.070.071
D-A0-0.070.071
E-A0-0.070.071
C-B0-0.070.071
D-B0-0.070.071
E-B0-0.070.071
D-C0-0.070.071
E-C0-0.070.071
E-D0-0.070.071
nee:A-ja:A0.3430.2260.4590
ja:B-ja:A0.1650.0490.2820.001
nee:B-ja:A0.1770.0610.2940
ja:C-ja:A0.2240.1080.3410
nee:C-ja:A0.1180.0020.2350.044
ja:D-ja:A0.3410.2250.4580
nee:D-ja:A0.001-0.1150.1181
ja:E-ja:A0.3980.2810.5140
nee:E-ja:A-0.055-0.1720.0610.847
ja:B-nee:A-0.177-0.294-0.0610
nee:B-nee:A-0.165-0.282-0.0490.001
ja:C-nee:A-0.118-0.235-0.0020.044
nee:C-nee:A-0.224-0.341-0.1080
ja:D-nee:A-0.001-0.1180.1151
nee:D-nee:A-0.341-0.458-0.2250
ja:E-nee:A0.055-0.0610.1720.847
nee:E-nee:A-0.398-0.514-0.2810
nee:B-ja:B0.012-0.1050.1281
ja:C-ja:B0.059-0.0570.1760.79
nee:C-ja:B-0.047-0.1640.0690.934
ja:D-ja:B0.1760.060.2930
nee:D-ja:B-0.164-0.281-0.0480.001
ja:E-ja:B0.2330.1160.3490
nee:E-ja:B-0.221-0.337-0.1040
ja:C-nee:B0.047-0.0690.1640.934
nee:C-nee:B-0.059-0.1760.0570.79
ja:D-nee:B0.1640.0480.2810.001
nee:D-nee:B-0.176-0.293-0.060
ja:E-nee:B0.2210.1040.3370
nee:E-nee:B-0.233-0.349-0.1160
nee:C-ja:C-0.106-0.2230.010.1
ja:D-ja:C0.1170.0010.2340.048
nee:D-ja:C-0.223-0.34-0.1070
ja:E-ja:C0.1730.0570.290
nee:E-ja:C-0.28-0.396-0.1630
ja:D-nee:C0.2230.1070.340
nee:D-nee:C-0.117-0.234-0.0010.048
ja:E-nee:C0.280.1630.3960
nee:E-nee:C-0.173-0.29-0.0570
nee:D-ja:D-0.34-0.457-0.2240
ja:E-ja:D0.056-0.060.1730.83
nee:E-ja:D-0.397-0.513-0.280
ja:E-nee:D0.3970.280.5130
nee:E-nee:D-0.056-0.1730.060.83
nee:E-ja:E-0.453-0.57-0.3370

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
nee-ja & -0.109 & -0.14 & -0.078 & 0 \tabularnewline
B-A & 0 & -0.07 & 0.07 & 1 \tabularnewline
C-A & 0 & -0.07 & 0.07 & 1 \tabularnewline
D-A & 0 & -0.07 & 0.07 & 1 \tabularnewline
E-A & 0 & -0.07 & 0.07 & 1 \tabularnewline
C-B & 0 & -0.07 & 0.07 & 1 \tabularnewline
D-B & 0 & -0.07 & 0.07 & 1 \tabularnewline
E-B & 0 & -0.07 & 0.07 & 1 \tabularnewline
D-C & 0 & -0.07 & 0.07 & 1 \tabularnewline
E-C & 0 & -0.07 & 0.07 & 1 \tabularnewline
E-D & 0 & -0.07 & 0.07 & 1 \tabularnewline
nee:A-ja:A & 0.343 & 0.226 & 0.459 & 0 \tabularnewline
ja:B-ja:A & 0.165 & 0.049 & 0.282 & 0.001 \tabularnewline
nee:B-ja:A & 0.177 & 0.061 & 0.294 & 0 \tabularnewline
ja:C-ja:A & 0.224 & 0.108 & 0.341 & 0 \tabularnewline
nee:C-ja:A & 0.118 & 0.002 & 0.235 & 0.044 \tabularnewline
ja:D-ja:A & 0.341 & 0.225 & 0.458 & 0 \tabularnewline
nee:D-ja:A & 0.001 & -0.115 & 0.118 & 1 \tabularnewline
ja:E-ja:A & 0.398 & 0.281 & 0.514 & 0 \tabularnewline
nee:E-ja:A & -0.055 & -0.172 & 0.061 & 0.847 \tabularnewline
ja:B-nee:A & -0.177 & -0.294 & -0.061 & 0 \tabularnewline
nee:B-nee:A & -0.165 & -0.282 & -0.049 & 0.001 \tabularnewline
ja:C-nee:A & -0.118 & -0.235 & -0.002 & 0.044 \tabularnewline
nee:C-nee:A & -0.224 & -0.341 & -0.108 & 0 \tabularnewline
ja:D-nee:A & -0.001 & -0.118 & 0.115 & 1 \tabularnewline
nee:D-nee:A & -0.341 & -0.458 & -0.225 & 0 \tabularnewline
ja:E-nee:A & 0.055 & -0.061 & 0.172 & 0.847 \tabularnewline
nee:E-nee:A & -0.398 & -0.514 & -0.281 & 0 \tabularnewline
nee:B-ja:B & 0.012 & -0.105 & 0.128 & 1 \tabularnewline
ja:C-ja:B & 0.059 & -0.057 & 0.176 & 0.79 \tabularnewline
nee:C-ja:B & -0.047 & -0.164 & 0.069 & 0.934 \tabularnewline
ja:D-ja:B & 0.176 & 0.06 & 0.293 & 0 \tabularnewline
nee:D-ja:B & -0.164 & -0.281 & -0.048 & 0.001 \tabularnewline
ja:E-ja:B & 0.233 & 0.116 & 0.349 & 0 \tabularnewline
nee:E-ja:B & -0.221 & -0.337 & -0.104 & 0 \tabularnewline
ja:C-nee:B & 0.047 & -0.069 & 0.164 & 0.934 \tabularnewline
nee:C-nee:B & -0.059 & -0.176 & 0.057 & 0.79 \tabularnewline
ja:D-nee:B & 0.164 & 0.048 & 0.281 & 0.001 \tabularnewline
nee:D-nee:B & -0.176 & -0.293 & -0.06 & 0 \tabularnewline
ja:E-nee:B & 0.221 & 0.104 & 0.337 & 0 \tabularnewline
nee:E-nee:B & -0.233 & -0.349 & -0.116 & 0 \tabularnewline
nee:C-ja:C & -0.106 & -0.223 & 0.01 & 0.1 \tabularnewline
ja:D-ja:C & 0.117 & 0.001 & 0.234 & 0.048 \tabularnewline
nee:D-ja:C & -0.223 & -0.34 & -0.107 & 0 \tabularnewline
ja:E-ja:C & 0.173 & 0.057 & 0.29 & 0 \tabularnewline
nee:E-ja:C & -0.28 & -0.396 & -0.163 & 0 \tabularnewline
ja:D-nee:C & 0.223 & 0.107 & 0.34 & 0 \tabularnewline
nee:D-nee:C & -0.117 & -0.234 & -0.001 & 0.048 \tabularnewline
ja:E-nee:C & 0.28 & 0.163 & 0.396 & 0 \tabularnewline
nee:E-nee:C & -0.173 & -0.29 & -0.057 & 0 \tabularnewline
nee:D-ja:D & -0.34 & -0.457 & -0.224 & 0 \tabularnewline
ja:E-ja:D & 0.056 & -0.06 & 0.173 & 0.83 \tabularnewline
nee:E-ja:D & -0.397 & -0.513 & -0.28 & 0 \tabularnewline
ja:E-nee:D & 0.397 & 0.28 & 0.513 & 0 \tabularnewline
nee:E-nee:D & -0.056 & -0.173 & 0.06 & 0.83 \tabularnewline
nee:E-ja:E & -0.453 & -0.57 & -0.337 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285169&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C] [/C][C]diff[/C][C]lwr[/C][C]upr[/C][C]p adj[/C][/ROW]
[ROW][C]nee-ja[/C][C]-0.109[/C][C]-0.14[/C][C]-0.078[/C][C]0[/C][/ROW]
[ROW][C]B-A[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]C-A[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]D-A[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]E-A[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]C-B[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]D-B[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]E-B[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]D-C[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]E-C[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]E-D[/C][C]0[/C][C]-0.07[/C][C]0.07[/C][C]1[/C][/ROW]
[ROW][C]nee:A-ja:A[/C][C]0.343[/C][C]0.226[/C][C]0.459[/C][C]0[/C][/ROW]
[ROW][C]ja:B-ja:A[/C][C]0.165[/C][C]0.049[/C][C]0.282[/C][C]0.001[/C][/ROW]
[ROW][C]nee:B-ja:A[/C][C]0.177[/C][C]0.061[/C][C]0.294[/C][C]0[/C][/ROW]
[ROW][C]ja:C-ja:A[/C][C]0.224[/C][C]0.108[/C][C]0.341[/C][C]0[/C][/ROW]
[ROW][C]nee:C-ja:A[/C][C]0.118[/C][C]0.002[/C][C]0.235[/C][C]0.044[/C][/ROW]
[ROW][C]ja:D-ja:A[/C][C]0.341[/C][C]0.225[/C][C]0.458[/C][C]0[/C][/ROW]
[ROW][C]nee:D-ja:A[/C][C]0.001[/C][C]-0.115[/C][C]0.118[/C][C]1[/C][/ROW]
[ROW][C]ja:E-ja:A[/C][C]0.398[/C][C]0.281[/C][C]0.514[/C][C]0[/C][/ROW]
[ROW][C]nee:E-ja:A[/C][C]-0.055[/C][C]-0.172[/C][C]0.061[/C][C]0.847[/C][/ROW]
[ROW][C]ja:B-nee:A[/C][C]-0.177[/C][C]-0.294[/C][C]-0.061[/C][C]0[/C][/ROW]
[ROW][C]nee:B-nee:A[/C][C]-0.165[/C][C]-0.282[/C][C]-0.049[/C][C]0.001[/C][/ROW]
[ROW][C]ja:C-nee:A[/C][C]-0.118[/C][C]-0.235[/C][C]-0.002[/C][C]0.044[/C][/ROW]
[ROW][C]nee:C-nee:A[/C][C]-0.224[/C][C]-0.341[/C][C]-0.108[/C][C]0[/C][/ROW]
[ROW][C]ja:D-nee:A[/C][C]-0.001[/C][C]-0.118[/C][C]0.115[/C][C]1[/C][/ROW]
[ROW][C]nee:D-nee:A[/C][C]-0.341[/C][C]-0.458[/C][C]-0.225[/C][C]0[/C][/ROW]
[ROW][C]ja:E-nee:A[/C][C]0.055[/C][C]-0.061[/C][C]0.172[/C][C]0.847[/C][/ROW]
[ROW][C]nee:E-nee:A[/C][C]-0.398[/C][C]-0.514[/C][C]-0.281[/C][C]0[/C][/ROW]
[ROW][C]nee:B-ja:B[/C][C]0.012[/C][C]-0.105[/C][C]0.128[/C][C]1[/C][/ROW]
[ROW][C]ja:C-ja:B[/C][C]0.059[/C][C]-0.057[/C][C]0.176[/C][C]0.79[/C][/ROW]
[ROW][C]nee:C-ja:B[/C][C]-0.047[/C][C]-0.164[/C][C]0.069[/C][C]0.934[/C][/ROW]
[ROW][C]ja:D-ja:B[/C][C]0.176[/C][C]0.06[/C][C]0.293[/C][C]0[/C][/ROW]
[ROW][C]nee:D-ja:B[/C][C]-0.164[/C][C]-0.281[/C][C]-0.048[/C][C]0.001[/C][/ROW]
[ROW][C]ja:E-ja:B[/C][C]0.233[/C][C]0.116[/C][C]0.349[/C][C]0[/C][/ROW]
[ROW][C]nee:E-ja:B[/C][C]-0.221[/C][C]-0.337[/C][C]-0.104[/C][C]0[/C][/ROW]
[ROW][C]ja:C-nee:B[/C][C]0.047[/C][C]-0.069[/C][C]0.164[/C][C]0.934[/C][/ROW]
[ROW][C]nee:C-nee:B[/C][C]-0.059[/C][C]-0.176[/C][C]0.057[/C][C]0.79[/C][/ROW]
[ROW][C]ja:D-nee:B[/C][C]0.164[/C][C]0.048[/C][C]0.281[/C][C]0.001[/C][/ROW]
[ROW][C]nee:D-nee:B[/C][C]-0.176[/C][C]-0.293[/C][C]-0.06[/C][C]0[/C][/ROW]
[ROW][C]ja:E-nee:B[/C][C]0.221[/C][C]0.104[/C][C]0.337[/C][C]0[/C][/ROW]
[ROW][C]nee:E-nee:B[/C][C]-0.233[/C][C]-0.349[/C][C]-0.116[/C][C]0[/C][/ROW]
[ROW][C]nee:C-ja:C[/C][C]-0.106[/C][C]-0.223[/C][C]0.01[/C][C]0.1[/C][/ROW]
[ROW][C]ja:D-ja:C[/C][C]0.117[/C][C]0.001[/C][C]0.234[/C][C]0.048[/C][/ROW]
[ROW][C]nee:D-ja:C[/C][C]-0.223[/C][C]-0.34[/C][C]-0.107[/C][C]0[/C][/ROW]
[ROW][C]ja:E-ja:C[/C][C]0.173[/C][C]0.057[/C][C]0.29[/C][C]0[/C][/ROW]
[ROW][C]nee:E-ja:C[/C][C]-0.28[/C][C]-0.396[/C][C]-0.163[/C][C]0[/C][/ROW]
[ROW][C]ja:D-nee:C[/C][C]0.223[/C][C]0.107[/C][C]0.34[/C][C]0[/C][/ROW]
[ROW][C]nee:D-nee:C[/C][C]-0.117[/C][C]-0.234[/C][C]-0.001[/C][C]0.048[/C][/ROW]
[ROW][C]ja:E-nee:C[/C][C]0.28[/C][C]0.163[/C][C]0.396[/C][C]0[/C][/ROW]
[ROW][C]nee:E-nee:C[/C][C]-0.173[/C][C]-0.29[/C][C]-0.057[/C][C]0[/C][/ROW]
[ROW][C]nee:D-ja:D[/C][C]-0.34[/C][C]-0.457[/C][C]-0.224[/C][C]0[/C][/ROW]
[ROW][C]ja:E-ja:D[/C][C]0.056[/C][C]-0.06[/C][C]0.173[/C][C]0.83[/C][/ROW]
[ROW][C]nee:E-ja:D[/C][C]-0.397[/C][C]-0.513[/C][C]-0.28[/C][C]0[/C][/ROW]
[ROW][C]ja:E-nee:D[/C][C]0.397[/C][C]0.28[/C][C]0.513[/C][C]0[/C][/ROW]
[ROW][C]nee:E-nee:D[/C][C]-0.056[/C][C]-0.173[/C][C]0.06[/C][C]0.83[/C][/ROW]
[ROW][C]nee:E-ja:E[/C][C]-0.453[/C][C]-0.57[/C][C]-0.337[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285169&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285169&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
nee-ja-0.109-0.14-0.0780
B-A0-0.070.071
C-A0-0.070.071
D-A0-0.070.071
E-A0-0.070.071
C-B0-0.070.071
D-B0-0.070.071
E-B0-0.070.071
D-C0-0.070.071
E-C0-0.070.071
E-D0-0.070.071
nee:A-ja:A0.3430.2260.4590
ja:B-ja:A0.1650.0490.2820.001
nee:B-ja:A0.1770.0610.2940
ja:C-ja:A0.2240.1080.3410
nee:C-ja:A0.1180.0020.2350.044
ja:D-ja:A0.3410.2250.4580
nee:D-ja:A0.001-0.1150.1181
ja:E-ja:A0.3980.2810.5140
nee:E-ja:A-0.055-0.1720.0610.847
ja:B-nee:A-0.177-0.294-0.0610
nee:B-nee:A-0.165-0.282-0.0490.001
ja:C-nee:A-0.118-0.235-0.0020.044
nee:C-nee:A-0.224-0.341-0.1080
ja:D-nee:A-0.001-0.1180.1151
nee:D-nee:A-0.341-0.458-0.2250
ja:E-nee:A0.055-0.0610.1720.847
nee:E-nee:A-0.398-0.514-0.2810
nee:B-ja:B0.012-0.1050.1281
ja:C-ja:B0.059-0.0570.1760.79
nee:C-ja:B-0.047-0.1640.0690.934
ja:D-ja:B0.1760.060.2930
nee:D-ja:B-0.164-0.281-0.0480.001
ja:E-ja:B0.2330.1160.3490
nee:E-ja:B-0.221-0.337-0.1040
ja:C-nee:B0.047-0.0690.1640.934
nee:C-nee:B-0.059-0.1760.0570.79
ja:D-nee:B0.1640.0480.2810.001
nee:D-nee:B-0.176-0.293-0.060
ja:E-nee:B0.2210.1040.3370
nee:E-nee:B-0.233-0.349-0.1160
nee:C-ja:C-0.106-0.2230.010.1
ja:D-ja:C0.1170.0010.2340.048
nee:D-ja:C-0.223-0.34-0.1070
ja:E-ja:C0.1730.0570.290
nee:E-ja:C-0.28-0.396-0.1630
ja:D-nee:C0.2230.1070.340
nee:D-nee:C-0.117-0.234-0.0010.048
ja:E-nee:C0.280.1630.3960
nee:E-nee:C-0.173-0.29-0.0570
nee:D-ja:D-0.34-0.457-0.2240
ja:E-ja:D0.056-0.060.1730.83
nee:E-ja:D-0.397-0.513-0.280
ja:E-nee:D0.3970.280.5130
nee:E-nee:D-0.056-0.1730.060.83
nee:E-ja:E-0.453-0.57-0.3370







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group90.3010.97
40

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 9 & 0.301 & 0.97 \tabularnewline
  & 40 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285169&T=4

[TABLE]
[ROW][C]Levenes Test for Homogeneity of Variance[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Group[/C][C]9[/C][C]0.301[/C][C]0.97[/C][/ROW]
[ROW][C] [/C][C]40[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285169&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285169&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group90.3010.97
40



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
cat3 <- as.numeric(par3)
intercept<-as.logical(par4)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
f2 <- as.character(x[,cat3])
xdf<-data.frame(x1,f1, f2)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
(V3 <-dimnames(y)[[1]][cat3])
names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, lmxdf$call['formula'],length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){
a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
for(i in 1 : length(rownames(anova.xdf))-1){
a<-table.row.start(a)
a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], digits=3),,FALSE)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$'Df'[i+1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups')
dev.off()
bitmap(file='designplot.png')
xdf2 <- xdf # to preserve xdf make copy for function
names(xdf2) <- c(V1, V2, V3)
plot.design(xdf2, main='Design Plot of Group Means')
dev.off()
bitmap(file='interactionplot.png')
interaction.plot(xdf$Treatment_A, xdf$Treatment_B, xdf$Response, xlab=V2, ylab=V1, trace.label=V3, main='Possible Interactions Between Anova Groups')
dev.off()
if(intercept==TRUE){
thsd<-TukeyHSD(aov.xdf)
names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep=''))
bitmap(file='TukeyHSDPlot.png')
layout(matrix(c(1,2,3,3), 2,2))
plot(thsd, las=1)
dev.off()
}
if(intercept==TRUE){
ntables<-length(names(thsd))
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(nt in 1:ntables){
for(i in 1:length(rownames(thsd[[nt]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[nt]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[nt]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
} # end nt
a<-table.end(a)
table.save(a,file='hsdtable.tab')
}#end if hsd tables
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-levene.test(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')