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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationTue, 08 Nov 2011 06:25:19 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/08/t1320751573h75f617wrf4pq3m.htm/, Retrieved Wed, 01 May 2024 21:55:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=140584, Retrieved Wed, 01 May 2024 21:55:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [Workshop 5 - Task...] [2011-11-08 11:25:19] [c897fb90cb9e1f725365d7e541ad7850] [Current]
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Dataseries X:
0	0	'WWE'
0	0	'WWE'
1	1	'WWE'
0	0	'WWE'
1	1	'WWE'
0	1	'WWE'
0	0	'WWE'
1	1	'WWE'
0	0	'WWE'
0	0	'WWE'
0	0	'WWE'
0	0	'WWE'
0	0	'WWE'
0	NA	'WWE'
0	1	'WWE'
0	NA	'WWE'
-1	-1	'WWE'
0	0	'WWE'
0	1	'WWE'
1	0	'WWE'
0	0	'WWE'
0	-1	'WWE'
0	0	'WWE'
1	0	'WWE'
1	1	'WWE'
1	1	'WWE'
0	0	'WWE'
0	-1	'WWE'
1	0	'WWE'
1	0	'WWE'
0	1	'WWE'
1	0	'WWE'
1	0	'WWE'
0	0	'WWE'
0	0	'WWE'
0	-1	'WWE'
0	-1	'WWE'
0	0	'WWE'
0	NA	'WWE'
0	1	'WWE'
0	0	'WWE'
0	0	'CSWE'
-1	NA	'CSWE'
0	0	'CSWE'
1	NA	'CSWE'
1	0	'CSWE'
0	0	'CSWE'
0	0	'CSWE'
0	1	'CSWE'
0	0	'CSWE'
0	-1	'CSWE'
0	1	'CSWE'
1	0	'CSWE'
0	0	'CSWE'
1	NA	'CSWE'
1	0	'CSWE'
1	NA	'CSWE'
0	-1	'CSWE'
1	0	'CSWE'
0	NA	'CSWE'
1	0	'CSWE'
0	0	'CSWE'
0	NA	'CSWE'
0	0	'CSWE'
1	0	'CSWE'
0	0	'CSWE'
0	1	'CSWE'
1	0	'CSWE'
1	0	'CSWE'
0	-1	'CSWE'
0	1	'CSWE'
1	1	'CSWE'
1	0	'CSWE'
0	NA	'CSWE'
0	0	'CSWE'
1	NA	'CSWE'
0	0	'CSWE'
0	0	'CSWE'
0	0	'CSWE'
1	0	'CSWE'
1	0	'CSWE'
0	0	'C'
0	1	'C'
-1	-1	'C'
0	1	'C'
0	NA	'C'
0	0	'C'
0	0	'C'
1	0	'C'
0	-1	'C'
0	NA	'C'
0	0	'C'
1	0	'C'
1	0	'C'
0	0	'C'
0	0	'C'
0	0	'C'
0	0	'C'
0	NA	'C'
0	0	'C'
1	0	'C'
0	-1	'C'
1	0	'C'
0	0	'C'
0	0	'C'
0	-1	'C'
0	0	'C'
0	0	'C'
0	0	'C'
0	0	'C'
0	0	'C'
0	-1	'C'
0	1	'C'
0	0	'C'
0	0	'C'
0	0	'C'
0	1	'C'
0	0	'C'
0	NA	'C'
0	-1	'C'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140584&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140584&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140584&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means-0.1670.3670.1670.1670.167-0.0330.0920.0330.2080.0940.5330.033

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & -0.167 & 0.367 & 0.167 & 0.167 & 0.167 & -0.033 & 0.092 & 0.033 & 0.208 & 0.094 & 0.533 & 0.033 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140584&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]-0.167[/C][C]0.367[/C][C]0.167[/C][C]0.167[/C][C]0.167[/C][C]-0.033[/C][C]0.092[/C][C]0.033[/C][C]0.208[/C][C]0.094[/C][C]0.533[/C][C]0.033[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140584&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140584&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
means-0.1670.3670.1670.1670.167-0.0330.0920.0330.2080.0940.5330.033







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
3
Treatment_A32.4940.8313.870.011
Treatment_B31.2340.6172.8720.061
Treatment_A:Treatment_B31.0620.1770.8240.554
Residuals10823.2010.215

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 3 &  &  &  &  \tabularnewline
Treatment_A & 3 & 2.494 & 0.831 & 3.87 & 0.011 \tabularnewline
Treatment_B & 3 & 1.234 & 0.617 & 2.872 & 0.061 \tabularnewline
Treatment_A:Treatment_B & 3 & 1.062 & 0.177 & 0.824 & 0.554 \tabularnewline
Residuals & 108 & 23.201 & 0.215 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140584&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]3[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]3[/C][C]2.494[/C][C]0.831[/C][C]3.87[/C][C]0.011[/C][/ROW]
[ROW][C]Treatment_B[/C][C]3[/C][C]1.234[/C][C]0.617[/C][C]2.872[/C][C]0.061[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]3[/C][C]1.062[/C][C]0.177[/C][C]0.824[/C][C]0.554[/C][/ROW]
[ROW][C]Residuals[/C][C]108[/C][C]23.201[/C][C]0.215[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140584&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140584&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)
3
Treatment_A32.4940.8313.870.011
Treatment_B31.2340.6172.8720.061
Treatment_A:Treatment_B31.0620.1770.8240.554
Residuals10823.2010.215







Tukey Honest Significant Difference Comparisons
difflwruprp adj
0--10.4480.0950.8020.007
1--10.4590.0330.8850.03
NA--10.343-0.1070.7920.198
1-00.01-0.3020.3221
NA-0-0.106-0.4490.2380.853
NA-1-0.116-0.5340.3020.888
CSWE-C0.247-0.0010.4950.051
WWE-C0.122-0.1240.3690.467
WWE-CSWE-0.125-0.3690.120.45
0:C--1:C0.367-0.3371.0710.845
1:C--1:C0.167-0.8331.1661
NA:C--1:C0.167-0.8331.1661
-1:CSWE--1:C0.167-0.9281.2621
0:CSWE--1:C0.625-0.0821.3320.137
1:CSWE--1:C0.367-0.5711.3040.977
NA:CSWE--1:C0.542-0.2951.3780.579
-1:WWE--1:C-0.033-0.9710.9041
0:WWE--1:C0.428-0.2821.1370.684
1:WWE--1:C0.667-0.1331.4660.201
NA:WWE--1:C0.167-0.9281.2621
1:C-0:C-0.2-1.0340.6341
NA:C-0:C-0.2-1.0340.6341
-1:CSWE-0:C-0.2-1.1460.7461
0:CSWE-0:C0.258-0.1840.7010.725
1:CSWE-0:C0-0.7590.7591
NA:CSWE-0:C0.175-0.4540.8040.999
-1:WWE-0:C-0.4-1.1590.3590.835
0:WWE-0:C0.061-0.3870.5081
1:WWE-0:C0.3-0.2790.8790.85
NA:WWE-0:C-0.2-1.1460.7461
NA:C-1:C0-1.0951.0951
-1:CSWE-1:C0-1.1831.1831
0:CSWE-1:C0.458-0.3781.2950.797
1:CSWE-1:C0.2-0.8391.2391
NA:CSWE-1:C0.375-0.5731.3230.975
-1:WWE-1:C-0.2-1.2390.8391
0:WWE-1:C0.261-0.5781.10.996
1:WWE-1:C0.5-0.4161.4160.802
NA:WWE-1:C0-1.1831.1831
-1:CSWE-NA:C0-1.1831.1831
0:CSWE-NA:C0.458-0.3781.2950.797
1:CSWE-NA:C0.2-0.8391.2391
NA:CSWE-NA:C0.375-0.5731.3230.975
-1:WWE-NA:C-0.2-1.2390.8391
0:WWE-NA:C0.261-0.5781.10.996
1:WWE-NA:C0.5-0.4161.4160.802
NA:WWE-NA:C0-1.1831.1831
0:CSWE--1:CSWE0.458-0.491.4070.9
1:CSWE--1:CSWE0.2-0.9311.3311
NA:CSWE--1:CSWE0.375-0.6731.4230.988
-1:WWE--1:CSWE-0.2-1.3310.9311
0:WWE--1:CSWE0.261-0.691.2110.999
1:WWE--1:CSWE0.5-0.5191.5190.891
NA:WWE--1:CSWE0-1.2641.2641
1:CSWE-0:CSWE-0.258-1.020.5030.992
NA:CSWE-0:CSWE-0.083-0.7160.5491
-1:WWE-0:CSWE-0.658-1.420.1030.16
0:WWE-0:CSWE-0.197-0.6490.2540.948
1:WWE-0:CSWE0.042-0.5410.6251
NA:WWE-0:CSWE-0.458-1.4070.490.9
NA:CSWE-1:CSWE0.175-0.7081.0581
-1:WWE-1:CSWE-0.4-1.3790.5790.968
0:WWE-1:CSWE0.061-0.7030.8251
1:WWE-1:CSWE0.3-0.5481.1480.989
NA:WWE-1:CSWE-0.2-1.3310.9311
-1:WWE-NA:CSWE-0.575-1.4580.3080.57
0:WWE-NA:CSWE-0.114-0.750.5211
1:WWE-NA:CSWE0.125-0.610.861
NA:WWE-NA:CSWE-0.375-1.4230.6730.988
0:WWE--1:WWE0.461-0.3031.2250.682
1:WWE--1:WWE0.7-0.1481.5480.214
NA:WWE--1:WWE0.2-0.9311.3311
1:WWE-0:WWE0.239-0.3470.8260.968
NA:WWE-0:WWE-0.261-1.2110.690.999
NA:WWE-1:WWE-0.5-1.5190.5190.891

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0--1 & 0.448 & 0.095 & 0.802 & 0.007 \tabularnewline
1--1 & 0.459 & 0.033 & 0.885 & 0.03 \tabularnewline
NA--1 & 0.343 & -0.107 & 0.792 & 0.198 \tabularnewline
1-0 & 0.01 & -0.302 & 0.322 & 1 \tabularnewline
NA-0 & -0.106 & -0.449 & 0.238 & 0.853 \tabularnewline
NA-1 & -0.116 & -0.534 & 0.302 & 0.888 \tabularnewline
CSWE-C & 0.247 & -0.001 & 0.495 & 0.051 \tabularnewline
WWE-C & 0.122 & -0.124 & 0.369 & 0.467 \tabularnewline
WWE-CSWE & -0.125 & -0.369 & 0.12 & 0.45 \tabularnewline
0:C--1:C & 0.367 & -0.337 & 1.071 & 0.845 \tabularnewline
1:C--1:C & 0.167 & -0.833 & 1.166 & 1 \tabularnewline
NA:C--1:C & 0.167 & -0.833 & 1.166 & 1 \tabularnewline
-1:CSWE--1:C & 0.167 & -0.928 & 1.262 & 1 \tabularnewline
0:CSWE--1:C & 0.625 & -0.082 & 1.332 & 0.137 \tabularnewline
1:CSWE--1:C & 0.367 & -0.571 & 1.304 & 0.977 \tabularnewline
NA:CSWE--1:C & 0.542 & -0.295 & 1.378 & 0.579 \tabularnewline
-1:WWE--1:C & -0.033 & -0.971 & 0.904 & 1 \tabularnewline
0:WWE--1:C & 0.428 & -0.282 & 1.137 & 0.684 \tabularnewline
1:WWE--1:C & 0.667 & -0.133 & 1.466 & 0.201 \tabularnewline
NA:WWE--1:C & 0.167 & -0.928 & 1.262 & 1 \tabularnewline
1:C-0:C & -0.2 & -1.034 & 0.634 & 1 \tabularnewline
NA:C-0:C & -0.2 & -1.034 & 0.634 & 1 \tabularnewline
-1:CSWE-0:C & -0.2 & -1.146 & 0.746 & 1 \tabularnewline
0:CSWE-0:C & 0.258 & -0.184 & 0.701 & 0.725 \tabularnewline
1:CSWE-0:C & 0 & -0.759 & 0.759 & 1 \tabularnewline
NA:CSWE-0:C & 0.175 & -0.454 & 0.804 & 0.999 \tabularnewline
-1:WWE-0:C & -0.4 & -1.159 & 0.359 & 0.835 \tabularnewline
0:WWE-0:C & 0.061 & -0.387 & 0.508 & 1 \tabularnewline
1:WWE-0:C & 0.3 & -0.279 & 0.879 & 0.85 \tabularnewline
NA:WWE-0:C & -0.2 & -1.146 & 0.746 & 1 \tabularnewline
NA:C-1:C & 0 & -1.095 & 1.095 & 1 \tabularnewline
-1:CSWE-1:C & 0 & -1.183 & 1.183 & 1 \tabularnewline
0:CSWE-1:C & 0.458 & -0.378 & 1.295 & 0.797 \tabularnewline
1:CSWE-1:C & 0.2 & -0.839 & 1.239 & 1 \tabularnewline
NA:CSWE-1:C & 0.375 & -0.573 & 1.323 & 0.975 \tabularnewline
-1:WWE-1:C & -0.2 & -1.239 & 0.839 & 1 \tabularnewline
0:WWE-1:C & 0.261 & -0.578 & 1.1 & 0.996 \tabularnewline
1:WWE-1:C & 0.5 & -0.416 & 1.416 & 0.802 \tabularnewline
NA:WWE-1:C & 0 & -1.183 & 1.183 & 1 \tabularnewline
-1:CSWE-NA:C & 0 & -1.183 & 1.183 & 1 \tabularnewline
0:CSWE-NA:C & 0.458 & -0.378 & 1.295 & 0.797 \tabularnewline
1:CSWE-NA:C & 0.2 & -0.839 & 1.239 & 1 \tabularnewline
NA:CSWE-NA:C & 0.375 & -0.573 & 1.323 & 0.975 \tabularnewline
-1:WWE-NA:C & -0.2 & -1.239 & 0.839 & 1 \tabularnewline
0:WWE-NA:C & 0.261 & -0.578 & 1.1 & 0.996 \tabularnewline
1:WWE-NA:C & 0.5 & -0.416 & 1.416 & 0.802 \tabularnewline
NA:WWE-NA:C & 0 & -1.183 & 1.183 & 1 \tabularnewline
0:CSWE--1:CSWE & 0.458 & -0.49 & 1.407 & 0.9 \tabularnewline
1:CSWE--1:CSWE & 0.2 & -0.931 & 1.331 & 1 \tabularnewline
NA:CSWE--1:CSWE & 0.375 & -0.673 & 1.423 & 0.988 \tabularnewline
-1:WWE--1:CSWE & -0.2 & -1.331 & 0.931 & 1 \tabularnewline
0:WWE--1:CSWE & 0.261 & -0.69 & 1.211 & 0.999 \tabularnewline
1:WWE--1:CSWE & 0.5 & -0.519 & 1.519 & 0.891 \tabularnewline
NA:WWE--1:CSWE & 0 & -1.264 & 1.264 & 1 \tabularnewline
1:CSWE-0:CSWE & -0.258 & -1.02 & 0.503 & 0.992 \tabularnewline
NA:CSWE-0:CSWE & -0.083 & -0.716 & 0.549 & 1 \tabularnewline
-1:WWE-0:CSWE & -0.658 & -1.42 & 0.103 & 0.16 \tabularnewline
0:WWE-0:CSWE & -0.197 & -0.649 & 0.254 & 0.948 \tabularnewline
1:WWE-0:CSWE & 0.042 & -0.541 & 0.625 & 1 \tabularnewline
NA:WWE-0:CSWE & -0.458 & -1.407 & 0.49 & 0.9 \tabularnewline
NA:CSWE-1:CSWE & 0.175 & -0.708 & 1.058 & 1 \tabularnewline
-1:WWE-1:CSWE & -0.4 & -1.379 & 0.579 & 0.968 \tabularnewline
0:WWE-1:CSWE & 0.061 & -0.703 & 0.825 & 1 \tabularnewline
1:WWE-1:CSWE & 0.3 & -0.548 & 1.148 & 0.989 \tabularnewline
NA:WWE-1:CSWE & -0.2 & -1.331 & 0.931 & 1 \tabularnewline
-1:WWE-NA:CSWE & -0.575 & -1.458 & 0.308 & 0.57 \tabularnewline
0:WWE-NA:CSWE & -0.114 & -0.75 & 0.521 & 1 \tabularnewline
1:WWE-NA:CSWE & 0.125 & -0.61 & 0.86 & 1 \tabularnewline
NA:WWE-NA:CSWE & -0.375 & -1.423 & 0.673 & 0.988 \tabularnewline
0:WWE--1:WWE & 0.461 & -0.303 & 1.225 & 0.682 \tabularnewline
1:WWE--1:WWE & 0.7 & -0.148 & 1.548 & 0.214 \tabularnewline
NA:WWE--1:WWE & 0.2 & -0.931 & 1.331 & 1 \tabularnewline
1:WWE-0:WWE & 0.239 & -0.347 & 0.826 & 0.968 \tabularnewline
NA:WWE-0:WWE & -0.261 & -1.211 & 0.69 & 0.999 \tabularnewline
NA:WWE-1:WWE & -0.5 & -1.519 & 0.519 & 0.891 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140584&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]0--1[/C][C]0.448[/C][C]0.095[/C][C]0.802[/C][C]0.007[/C][/ROW]
[ROW][C]1--1[/C][C]0.459[/C][C]0.033[/C][C]0.885[/C][C]0.03[/C][/ROW]
[ROW][C]NA--1[/C][C]0.343[/C][C]-0.107[/C][C]0.792[/C][C]0.198[/C][/ROW]
[ROW][C]1-0[/C][C]0.01[/C][C]-0.302[/C][C]0.322[/C][C]1[/C][/ROW]
[ROW][C]NA-0[/C][C]-0.106[/C][C]-0.449[/C][C]0.238[/C][C]0.853[/C][/ROW]
[ROW][C]NA-1[/C][C]-0.116[/C][C]-0.534[/C][C]0.302[/C][C]0.888[/C][/ROW]
[ROW][C]CSWE-C[/C][C]0.247[/C][C]-0.001[/C][C]0.495[/C][C]0.051[/C][/ROW]
[ROW][C]WWE-C[/C][C]0.122[/C][C]-0.124[/C][C]0.369[/C][C]0.467[/C][/ROW]
[ROW][C]WWE-CSWE[/C][C]-0.125[/C][C]-0.369[/C][C]0.12[/C][C]0.45[/C][/ROW]
[ROW][C]0:C--1:C[/C][C]0.367[/C][C]-0.337[/C][C]1.071[/C][C]0.845[/C][/ROW]
[ROW][C]1:C--1:C[/C][C]0.167[/C][C]-0.833[/C][C]1.166[/C][C]1[/C][/ROW]
[ROW][C]NA:C--1:C[/C][C]0.167[/C][C]-0.833[/C][C]1.166[/C][C]1[/C][/ROW]
[ROW][C]-1:CSWE--1:C[/C][C]0.167[/C][C]-0.928[/C][C]1.262[/C][C]1[/C][/ROW]
[ROW][C]0:CSWE--1:C[/C][C]0.625[/C][C]-0.082[/C][C]1.332[/C][C]0.137[/C][/ROW]
[ROW][C]1:CSWE--1:C[/C][C]0.367[/C][C]-0.571[/C][C]1.304[/C][C]0.977[/C][/ROW]
[ROW][C]NA:CSWE--1:C[/C][C]0.542[/C][C]-0.295[/C][C]1.378[/C][C]0.579[/C][/ROW]
[ROW][C]-1:WWE--1:C[/C][C]-0.033[/C][C]-0.971[/C][C]0.904[/C][C]1[/C][/ROW]
[ROW][C]0:WWE--1:C[/C][C]0.428[/C][C]-0.282[/C][C]1.137[/C][C]0.684[/C][/ROW]
[ROW][C]1:WWE--1:C[/C][C]0.667[/C][C]-0.133[/C][C]1.466[/C][C]0.201[/C][/ROW]
[ROW][C]NA:WWE--1:C[/C][C]0.167[/C][C]-0.928[/C][C]1.262[/C][C]1[/C][/ROW]
[ROW][C]1:C-0:C[/C][C]-0.2[/C][C]-1.034[/C][C]0.634[/C][C]1[/C][/ROW]
[ROW][C]NA:C-0:C[/C][C]-0.2[/C][C]-1.034[/C][C]0.634[/C][C]1[/C][/ROW]
[ROW][C]-1:CSWE-0:C[/C][C]-0.2[/C][C]-1.146[/C][C]0.746[/C][C]1[/C][/ROW]
[ROW][C]0:CSWE-0:C[/C][C]0.258[/C][C]-0.184[/C][C]0.701[/C][C]0.725[/C][/ROW]
[ROW][C]1:CSWE-0:C[/C][C]0[/C][C]-0.759[/C][C]0.759[/C][C]1[/C][/ROW]
[ROW][C]NA:CSWE-0:C[/C][C]0.175[/C][C]-0.454[/C][C]0.804[/C][C]0.999[/C][/ROW]
[ROW][C]-1:WWE-0:C[/C][C]-0.4[/C][C]-1.159[/C][C]0.359[/C][C]0.835[/C][/ROW]
[ROW][C]0:WWE-0:C[/C][C]0.061[/C][C]-0.387[/C][C]0.508[/C][C]1[/C][/ROW]
[ROW][C]1:WWE-0:C[/C][C]0.3[/C][C]-0.279[/C][C]0.879[/C][C]0.85[/C][/ROW]
[ROW][C]NA:WWE-0:C[/C][C]-0.2[/C][C]-1.146[/C][C]0.746[/C][C]1[/C][/ROW]
[ROW][C]NA:C-1:C[/C][C]0[/C][C]-1.095[/C][C]1.095[/C][C]1[/C][/ROW]
[ROW][C]-1:CSWE-1:C[/C][C]0[/C][C]-1.183[/C][C]1.183[/C][C]1[/C][/ROW]
[ROW][C]0:CSWE-1:C[/C][C]0.458[/C][C]-0.378[/C][C]1.295[/C][C]0.797[/C][/ROW]
[ROW][C]1:CSWE-1:C[/C][C]0.2[/C][C]-0.839[/C][C]1.239[/C][C]1[/C][/ROW]
[ROW][C]NA:CSWE-1:C[/C][C]0.375[/C][C]-0.573[/C][C]1.323[/C][C]0.975[/C][/ROW]
[ROW][C]-1:WWE-1:C[/C][C]-0.2[/C][C]-1.239[/C][C]0.839[/C][C]1[/C][/ROW]
[ROW][C]0:WWE-1:C[/C][C]0.261[/C][C]-0.578[/C][C]1.1[/C][C]0.996[/C][/ROW]
[ROW][C]1:WWE-1:C[/C][C]0.5[/C][C]-0.416[/C][C]1.416[/C][C]0.802[/C][/ROW]
[ROW][C]NA:WWE-1:C[/C][C]0[/C][C]-1.183[/C][C]1.183[/C][C]1[/C][/ROW]
[ROW][C]-1:CSWE-NA:C[/C][C]0[/C][C]-1.183[/C][C]1.183[/C][C]1[/C][/ROW]
[ROW][C]0:CSWE-NA:C[/C][C]0.458[/C][C]-0.378[/C][C]1.295[/C][C]0.797[/C][/ROW]
[ROW][C]1:CSWE-NA:C[/C][C]0.2[/C][C]-0.839[/C][C]1.239[/C][C]1[/C][/ROW]
[ROW][C]NA:CSWE-NA:C[/C][C]0.375[/C][C]-0.573[/C][C]1.323[/C][C]0.975[/C][/ROW]
[ROW][C]-1:WWE-NA:C[/C][C]-0.2[/C][C]-1.239[/C][C]0.839[/C][C]1[/C][/ROW]
[ROW][C]0:WWE-NA:C[/C][C]0.261[/C][C]-0.578[/C][C]1.1[/C][C]0.996[/C][/ROW]
[ROW][C]1:WWE-NA:C[/C][C]0.5[/C][C]-0.416[/C][C]1.416[/C][C]0.802[/C][/ROW]
[ROW][C]NA:WWE-NA:C[/C][C]0[/C][C]-1.183[/C][C]1.183[/C][C]1[/C][/ROW]
[ROW][C]0:CSWE--1:CSWE[/C][C]0.458[/C][C]-0.49[/C][C]1.407[/C][C]0.9[/C][/ROW]
[ROW][C]1:CSWE--1:CSWE[/C][C]0.2[/C][C]-0.931[/C][C]1.331[/C][C]1[/C][/ROW]
[ROW][C]NA:CSWE--1:CSWE[/C][C]0.375[/C][C]-0.673[/C][C]1.423[/C][C]0.988[/C][/ROW]
[ROW][C]-1:WWE--1:CSWE[/C][C]-0.2[/C][C]-1.331[/C][C]0.931[/C][C]1[/C][/ROW]
[ROW][C]0:WWE--1:CSWE[/C][C]0.261[/C][C]-0.69[/C][C]1.211[/C][C]0.999[/C][/ROW]
[ROW][C]1:WWE--1:CSWE[/C][C]0.5[/C][C]-0.519[/C][C]1.519[/C][C]0.891[/C][/ROW]
[ROW][C]NA:WWE--1:CSWE[/C][C]0[/C][C]-1.264[/C][C]1.264[/C][C]1[/C][/ROW]
[ROW][C]1:CSWE-0:CSWE[/C][C]-0.258[/C][C]-1.02[/C][C]0.503[/C][C]0.992[/C][/ROW]
[ROW][C]NA:CSWE-0:CSWE[/C][C]-0.083[/C][C]-0.716[/C][C]0.549[/C][C]1[/C][/ROW]
[ROW][C]-1:WWE-0:CSWE[/C][C]-0.658[/C][C]-1.42[/C][C]0.103[/C][C]0.16[/C][/ROW]
[ROW][C]0:WWE-0:CSWE[/C][C]-0.197[/C][C]-0.649[/C][C]0.254[/C][C]0.948[/C][/ROW]
[ROW][C]1:WWE-0:CSWE[/C][C]0.042[/C][C]-0.541[/C][C]0.625[/C][C]1[/C][/ROW]
[ROW][C]NA:WWE-0:CSWE[/C][C]-0.458[/C][C]-1.407[/C][C]0.49[/C][C]0.9[/C][/ROW]
[ROW][C]NA:CSWE-1:CSWE[/C][C]0.175[/C][C]-0.708[/C][C]1.058[/C][C]1[/C][/ROW]
[ROW][C]-1:WWE-1:CSWE[/C][C]-0.4[/C][C]-1.379[/C][C]0.579[/C][C]0.968[/C][/ROW]
[ROW][C]0:WWE-1:CSWE[/C][C]0.061[/C][C]-0.703[/C][C]0.825[/C][C]1[/C][/ROW]
[ROW][C]1:WWE-1:CSWE[/C][C]0.3[/C][C]-0.548[/C][C]1.148[/C][C]0.989[/C][/ROW]
[ROW][C]NA:WWE-1:CSWE[/C][C]-0.2[/C][C]-1.331[/C][C]0.931[/C][C]1[/C][/ROW]
[ROW][C]-1:WWE-NA:CSWE[/C][C]-0.575[/C][C]-1.458[/C][C]0.308[/C][C]0.57[/C][/ROW]
[ROW][C]0:WWE-NA:CSWE[/C][C]-0.114[/C][C]-0.75[/C][C]0.521[/C][C]1[/C][/ROW]
[ROW][C]1:WWE-NA:CSWE[/C][C]0.125[/C][C]-0.61[/C][C]0.86[/C][C]1[/C][/ROW]
[ROW][C]NA:WWE-NA:CSWE[/C][C]-0.375[/C][C]-1.423[/C][C]0.673[/C][C]0.988[/C][/ROW]
[ROW][C]0:WWE--1:WWE[/C][C]0.461[/C][C]-0.303[/C][C]1.225[/C][C]0.682[/C][/ROW]
[ROW][C]1:WWE--1:WWE[/C][C]0.7[/C][C]-0.148[/C][C]1.548[/C][C]0.214[/C][/ROW]
[ROW][C]NA:WWE--1:WWE[/C][C]0.2[/C][C]-0.931[/C][C]1.331[/C][C]1[/C][/ROW]
[ROW][C]1:WWE-0:WWE[/C][C]0.239[/C][C]-0.347[/C][C]0.826[/C][C]0.968[/C][/ROW]
[ROW][C]NA:WWE-0:WWE[/C][C]-0.261[/C][C]-1.211[/C][C]0.69[/C][C]0.999[/C][/ROW]
[ROW][C]NA:WWE-1:WWE[/C][C]-0.5[/C][C]-1.519[/C][C]0.519[/C][C]0.891[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140584&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140584&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
0--10.4480.0950.8020.007
1--10.4590.0330.8850.03
NA--10.343-0.1070.7920.198
1-00.01-0.3020.3221
NA-0-0.106-0.4490.2380.853
NA-1-0.116-0.5340.3020.888
CSWE-C0.247-0.0010.4950.051
WWE-C0.122-0.1240.3690.467
WWE-CSWE-0.125-0.3690.120.45
0:C--1:C0.367-0.3371.0710.845
1:C--1:C0.167-0.8331.1661
NA:C--1:C0.167-0.8331.1661
-1:CSWE--1:C0.167-0.9281.2621
0:CSWE--1:C0.625-0.0821.3320.137
1:CSWE--1:C0.367-0.5711.3040.977
NA:CSWE--1:C0.542-0.2951.3780.579
-1:WWE--1:C-0.033-0.9710.9041
0:WWE--1:C0.428-0.2821.1370.684
1:WWE--1:C0.667-0.1331.4660.201
NA:WWE--1:C0.167-0.9281.2621
1:C-0:C-0.2-1.0340.6341
NA:C-0:C-0.2-1.0340.6341
-1:CSWE-0:C-0.2-1.1460.7461
0:CSWE-0:C0.258-0.1840.7010.725
1:CSWE-0:C0-0.7590.7591
NA:CSWE-0:C0.175-0.4540.8040.999
-1:WWE-0:C-0.4-1.1590.3590.835
0:WWE-0:C0.061-0.3870.5081
1:WWE-0:C0.3-0.2790.8790.85
NA:WWE-0:C-0.2-1.1460.7461
NA:C-1:C0-1.0951.0951
-1:CSWE-1:C0-1.1831.1831
0:CSWE-1:C0.458-0.3781.2950.797
1:CSWE-1:C0.2-0.8391.2391
NA:CSWE-1:C0.375-0.5731.3230.975
-1:WWE-1:C-0.2-1.2390.8391
0:WWE-1:C0.261-0.5781.10.996
1:WWE-1:C0.5-0.4161.4160.802
NA:WWE-1:C0-1.1831.1831
-1:CSWE-NA:C0-1.1831.1831
0:CSWE-NA:C0.458-0.3781.2950.797
1:CSWE-NA:C0.2-0.8391.2391
NA:CSWE-NA:C0.375-0.5731.3230.975
-1:WWE-NA:C-0.2-1.2390.8391
0:WWE-NA:C0.261-0.5781.10.996
1:WWE-NA:C0.5-0.4161.4160.802
NA:WWE-NA:C0-1.1831.1831
0:CSWE--1:CSWE0.458-0.491.4070.9
1:CSWE--1:CSWE0.2-0.9311.3311
NA:CSWE--1:CSWE0.375-0.6731.4230.988
-1:WWE--1:CSWE-0.2-1.3310.9311
0:WWE--1:CSWE0.261-0.691.2110.999
1:WWE--1:CSWE0.5-0.5191.5190.891
NA:WWE--1:CSWE0-1.2641.2641
1:CSWE-0:CSWE-0.258-1.020.5030.992
NA:CSWE-0:CSWE-0.083-0.7160.5491
-1:WWE-0:CSWE-0.658-1.420.1030.16
0:WWE-0:CSWE-0.197-0.6490.2540.948
1:WWE-0:CSWE0.042-0.5410.6251
NA:WWE-0:CSWE-0.458-1.4070.490.9
NA:CSWE-1:CSWE0.175-0.7081.0581
-1:WWE-1:CSWE-0.4-1.3790.5790.968
0:WWE-1:CSWE0.061-0.7030.8251
1:WWE-1:CSWE0.3-0.5481.1480.989
NA:WWE-1:CSWE-0.2-1.3310.9311
-1:WWE-NA:CSWE-0.575-1.4580.3080.57
0:WWE-NA:CSWE-0.114-0.750.5211
1:WWE-NA:CSWE0.125-0.610.861
NA:WWE-NA:CSWE-0.375-1.4230.6730.988
0:WWE--1:WWE0.461-0.3031.2250.682
1:WWE--1:WWE0.7-0.1481.5480.214
NA:WWE--1:WWE0.2-0.9311.3311
1:WWE-0:WWE0.239-0.3470.8260.968
NA:WWE-0:WWE-0.261-1.2110.690.999
NA:WWE-1:WWE-0.5-1.5190.5190.891







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group111.9910.036
108

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 11 & 1.991 & 0.036 \tabularnewline
  & 108 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140584&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]11[/C][C]1.991[/C][C]0.036[/C][/ROW]
[ROW][C] [/C][C]108[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140584&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140584&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)
Group111.9910.036
108



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')