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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 computationMon, 01 Nov 2010 19:36:55 +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/2010/Nov/01/t1288640215q25okr037w7zc6q.htm/, Retrieved Mon, 29 Apr 2024 12:18:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=91073, Retrieved Mon, 29 Apr 2024 12:18:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [Golfballs] [2010-10-25 12:43:22] [b98453cac15ba1066b407e146608df68]
- R PD  [Two-Way ANOVA] [] [2010-10-30 13:24:48] [39e83c7b0ac936e906a817a1bb402750]
-   P       [Two-Way ANOVA] [W5 Q7] [2010-11-01 19:36:55] [cda497ce08bc921f0aec22acd67c882b] [Current]
-    D        [Two-Way ANOVA] [W5 Q8] [2010-11-01 19:44:21] [b1e5ec7263cdefe98ec76e1a1363de05]
Feedback Forum

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Dataseries X:
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
1	 'pre'	'WWE'
1	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
1	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
1	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
1	 'pre'	'WWE'
1	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'WWE'
0	 'pre'	'CSWE'
1	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
1	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
1	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
1	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'CSWE'
0	 'pre'	'C'
0	 'pre'	'C'
1	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
1	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
1	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
1	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
1	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
0	 'pre'	'C'
1	 'pre'	'C'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
1	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
1	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
1	 'post1'	'WWE'
1	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'WWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
0	 'post1'	'CSWE'
1	 'post1'	'CSWE'
1	 'post1'	'CSWE'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
1	 'post1'	'C'
1	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
1	 'post1'	'C'
1	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
1	 'post1'	'C'
1	 'post1'	'C'
1	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
1	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
1	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
0	 'post1'	'C'
1	 'post1'	'C'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
1	 'post2'	'WWE'
0	 'post2'	'WWE'
1	 'post2'	'WWE'
1	 'post2'	'WWE'
0	 'post2'	'WWE'
1	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
NA	 'post2'	'WWE'
1	 'post2'	'WWE'
NA	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
1	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
1	 'post2'	'WWE'
1	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
1	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'WWE'
NA	 'post2'	'WWE'
1	 'post2'	'WWE'
0	 'post2'	'WWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
1	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
1	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
1	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
1	 'post2'	'CSWE'
1	 'post2'	'CSWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
NA	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'CSWE'
0	 'post2'	'C'
1	 'post2'	'C'
0	 'post2'	'C'
1	 'post2'	'C'
NA	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
NA	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
NA	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
1	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
0	 'post2'	'C'
1	 'post2'	'C'
0	 'post2'	'C'
NA	 'post2'	'C'
0	 'post2'	'C'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91073&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91073&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91073&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.256-0.142-0.1030.2190.134-0.177-0.2720.015-0.141

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 0.256 & -0.142 & -0.103 & 0.219 & 0.134 & -0.177 & -0.272 & 0.015 & -0.141 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91073&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]0.256[/C][C]-0.142[/C][C]-0.103[/C][C]0.219[/C][C]0.134[/C][C]-0.177[/C][C]-0.272[/C][C]0.015[/C][C]-0.141[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91073&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91073&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
means0.256-0.142-0.1030.2190.134-0.177-0.2720.015-0.141







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A23.8961.94811.6670
Treatment_B20.520.261.5570.212
Treatment_A:Treatment_B20.9380.2341.4040.232
Residuals33656.0960.167

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 3.896 & 1.948 & 11.667 & 0 \tabularnewline
Treatment_B & 2 & 0.52 & 0.26 & 1.557 & 0.212 \tabularnewline
Treatment_A:Treatment_B & 2 & 0.938 & 0.234 & 1.404 & 0.232 \tabularnewline
Residuals & 336 & 56.096 & 0.167 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91073&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]2[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]2[/C][C]3.896[/C][C]1.948[/C][C]11.667[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]0.52[/C][C]0.26[/C][C]1.557[/C][C]0.212[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]0.938[/C][C]0.234[/C][C]1.404[/C][C]0.232[/C][/ROW]
[ROW][C]Residuals[/C][C]336[/C][C]56.096[/C][C]0.167[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91073&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91073&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)
2
Treatment_A23.8961.94811.6670
Treatment_B20.520.261.5570.212
Treatment_A:Treatment_B20.9380.2341.4040.232
Residuals33656.0960.167







Tukey Honest Significant Difference Comparisons
difflwruprp adj
post2-post1-0.194-0.323-0.0660.001
pre-post1-0.242-0.366-0.1170
pre-post2-0.048-0.1760.0810.658
CSWE-C0.071-0.0570.20.392
WWE-C0.09-0.0360.2160.213
WWE-CSWE0.019-0.1070.1450.934
post2:C-post1:C-0.142-0.4390.1550.858
pre:C-post1:C-0.103-0.3910.1860.973
post1:CSWE-post1:C0.219-0.0680.5060.3
post2:CSWE-post1:C-0.1-0.4040.2040.983
pre:CSWE-post1:C-0.156-0.4430.1310.746
post1:WWE-post1:C0.134-0.1520.4190.871
post2:WWE-post1:C0.007-0.2840.2981
pre:WWE-post1:C-0.11-0.3950.1750.955
pre:C-post2:C0.04-0.2570.3371
post1:CSWE-post2:C0.3610.0650.6560.005
post2:CSWE-post2:C0.042-0.270.3541
pre:CSWE-post2:C-0.014-0.310.2811
post1:WWE-post2:C0.276-0.0180.570.084
post2:WWE-post2:C0.149-0.150.4480.828
pre:WWE-post2:C0.032-0.2620.3261
post1:CSWE-pre:C0.3210.0340.6080.016
post2:CSWE-pre:C0.002-0.3020.3071
pre:CSWE-pre:C-0.054-0.3410.2331
post1:WWE-pre:C0.236-0.0490.5220.196
post2:WWE-pre:C0.109-0.1810.40.962
pre:WWE-pre:C-0.008-0.2930.2781
post2:CSWE-post1:CSWE-0.319-0.621-0.0160.03
pre:CSWE-post1:CSWE-0.375-0.66-0.090.002
post1:WWE-post1:CSWE-0.085-0.3680.1990.991
post2:WWE-post1:CSWE-0.212-0.5010.0770.352
pre:WWE-post1:CSWE-0.329-0.612-0.0450.01
pre:CSWE-post2:CSWE-0.056-0.3590.2461
post1:WWE-post2:CSWE0.234-0.0670.5350.272
post2:WWE-post2:CSWE0.107-0.1990.4130.975
pre:WWE-post2:CSWE-0.01-0.3110.2911
post1:WWE-pre:CSWE0.290.0070.5740.04
post2:WWE-pre:CSWE0.163-0.1260.4520.707
pre:WWE-pre:CSWE0.046-0.2370.331
post2:WWE-post1:WWE-0.127-0.4140.160.904
pre:WWE-post1:WWE-0.244-0.5260.0380.151
pre:WWE-post2:WWE-0.117-0.4040.170.939

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
post2-post1 & -0.194 & -0.323 & -0.066 & 0.001 \tabularnewline
pre-post1 & -0.242 & -0.366 & -0.117 & 0 \tabularnewline
pre-post2 & -0.048 & -0.176 & 0.081 & 0.658 \tabularnewline
CSWE-C & 0.071 & -0.057 & 0.2 & 0.392 \tabularnewline
WWE-C & 0.09 & -0.036 & 0.216 & 0.213 \tabularnewline
WWE-CSWE & 0.019 & -0.107 & 0.145 & 0.934 \tabularnewline
post2:C-post1:C & -0.142 & -0.439 & 0.155 & 0.858 \tabularnewline
pre:C-post1:C & -0.103 & -0.391 & 0.186 & 0.973 \tabularnewline
post1:CSWE-post1:C & 0.219 & -0.068 & 0.506 & 0.3 \tabularnewline
post2:CSWE-post1:C & -0.1 & -0.404 & 0.204 & 0.983 \tabularnewline
pre:CSWE-post1:C & -0.156 & -0.443 & 0.131 & 0.746 \tabularnewline
post1:WWE-post1:C & 0.134 & -0.152 & 0.419 & 0.871 \tabularnewline
post2:WWE-post1:C & 0.007 & -0.284 & 0.298 & 1 \tabularnewline
pre:WWE-post1:C & -0.11 & -0.395 & 0.175 & 0.955 \tabularnewline
pre:C-post2:C & 0.04 & -0.257 & 0.337 & 1 \tabularnewline
post1:CSWE-post2:C & 0.361 & 0.065 & 0.656 & 0.005 \tabularnewline
post2:CSWE-post2:C & 0.042 & -0.27 & 0.354 & 1 \tabularnewline
pre:CSWE-post2:C & -0.014 & -0.31 & 0.281 & 1 \tabularnewline
post1:WWE-post2:C & 0.276 & -0.018 & 0.57 & 0.084 \tabularnewline
post2:WWE-post2:C & 0.149 & -0.15 & 0.448 & 0.828 \tabularnewline
pre:WWE-post2:C & 0.032 & -0.262 & 0.326 & 1 \tabularnewline
post1:CSWE-pre:C & 0.321 & 0.034 & 0.608 & 0.016 \tabularnewline
post2:CSWE-pre:C & 0.002 & -0.302 & 0.307 & 1 \tabularnewline
pre:CSWE-pre:C & -0.054 & -0.341 & 0.233 & 1 \tabularnewline
post1:WWE-pre:C & 0.236 & -0.049 & 0.522 & 0.196 \tabularnewline
post2:WWE-pre:C & 0.109 & -0.181 & 0.4 & 0.962 \tabularnewline
pre:WWE-pre:C & -0.008 & -0.293 & 0.278 & 1 \tabularnewline
post2:CSWE-post1:CSWE & -0.319 & -0.621 & -0.016 & 0.03 \tabularnewline
pre:CSWE-post1:CSWE & -0.375 & -0.66 & -0.09 & 0.002 \tabularnewline
post1:WWE-post1:CSWE & -0.085 & -0.368 & 0.199 & 0.991 \tabularnewline
post2:WWE-post1:CSWE & -0.212 & -0.501 & 0.077 & 0.352 \tabularnewline
pre:WWE-post1:CSWE & -0.329 & -0.612 & -0.045 & 0.01 \tabularnewline
pre:CSWE-post2:CSWE & -0.056 & -0.359 & 0.246 & 1 \tabularnewline
post1:WWE-post2:CSWE & 0.234 & -0.067 & 0.535 & 0.272 \tabularnewline
post2:WWE-post2:CSWE & 0.107 & -0.199 & 0.413 & 0.975 \tabularnewline
pre:WWE-post2:CSWE & -0.01 & -0.311 & 0.291 & 1 \tabularnewline
post1:WWE-pre:CSWE & 0.29 & 0.007 & 0.574 & 0.04 \tabularnewline
post2:WWE-pre:CSWE & 0.163 & -0.126 & 0.452 & 0.707 \tabularnewline
pre:WWE-pre:CSWE & 0.046 & -0.237 & 0.33 & 1 \tabularnewline
post2:WWE-post1:WWE & -0.127 & -0.414 & 0.16 & 0.904 \tabularnewline
pre:WWE-post1:WWE & -0.244 & -0.526 & 0.038 & 0.151 \tabularnewline
pre:WWE-post2:WWE & -0.117 & -0.404 & 0.17 & 0.939 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91073&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]post2-post1[/C][C]-0.194[/C][C]-0.323[/C][C]-0.066[/C][C]0.001[/C][/ROW]
[ROW][C]pre-post1[/C][C]-0.242[/C][C]-0.366[/C][C]-0.117[/C][C]0[/C][/ROW]
[ROW][C]pre-post2[/C][C]-0.048[/C][C]-0.176[/C][C]0.081[/C][C]0.658[/C][/ROW]
[ROW][C]CSWE-C[/C][C]0.071[/C][C]-0.057[/C][C]0.2[/C][C]0.392[/C][/ROW]
[ROW][C]WWE-C[/C][C]0.09[/C][C]-0.036[/C][C]0.216[/C][C]0.213[/C][/ROW]
[ROW][C]WWE-CSWE[/C][C]0.019[/C][C]-0.107[/C][C]0.145[/C][C]0.934[/C][/ROW]
[ROW][C]post2:C-post1:C[/C][C]-0.142[/C][C]-0.439[/C][C]0.155[/C][C]0.858[/C][/ROW]
[ROW][C]pre:C-post1:C[/C][C]-0.103[/C][C]-0.391[/C][C]0.186[/C][C]0.973[/C][/ROW]
[ROW][C]post1:CSWE-post1:C[/C][C]0.219[/C][C]-0.068[/C][C]0.506[/C][C]0.3[/C][/ROW]
[ROW][C]post2:CSWE-post1:C[/C][C]-0.1[/C][C]-0.404[/C][C]0.204[/C][C]0.983[/C][/ROW]
[ROW][C]pre:CSWE-post1:C[/C][C]-0.156[/C][C]-0.443[/C][C]0.131[/C][C]0.746[/C][/ROW]
[ROW][C]post1:WWE-post1:C[/C][C]0.134[/C][C]-0.152[/C][C]0.419[/C][C]0.871[/C][/ROW]
[ROW][C]post2:WWE-post1:C[/C][C]0.007[/C][C]-0.284[/C][C]0.298[/C][C]1[/C][/ROW]
[ROW][C]pre:WWE-post1:C[/C][C]-0.11[/C][C]-0.395[/C][C]0.175[/C][C]0.955[/C][/ROW]
[ROW][C]pre:C-post2:C[/C][C]0.04[/C][C]-0.257[/C][C]0.337[/C][C]1[/C][/ROW]
[ROW][C]post1:CSWE-post2:C[/C][C]0.361[/C][C]0.065[/C][C]0.656[/C][C]0.005[/C][/ROW]
[ROW][C]post2:CSWE-post2:C[/C][C]0.042[/C][C]-0.27[/C][C]0.354[/C][C]1[/C][/ROW]
[ROW][C]pre:CSWE-post2:C[/C][C]-0.014[/C][C]-0.31[/C][C]0.281[/C][C]1[/C][/ROW]
[ROW][C]post1:WWE-post2:C[/C][C]0.276[/C][C]-0.018[/C][C]0.57[/C][C]0.084[/C][/ROW]
[ROW][C]post2:WWE-post2:C[/C][C]0.149[/C][C]-0.15[/C][C]0.448[/C][C]0.828[/C][/ROW]
[ROW][C]pre:WWE-post2:C[/C][C]0.032[/C][C]-0.262[/C][C]0.326[/C][C]1[/C][/ROW]
[ROW][C]post1:CSWE-pre:C[/C][C]0.321[/C][C]0.034[/C][C]0.608[/C][C]0.016[/C][/ROW]
[ROW][C]post2:CSWE-pre:C[/C][C]0.002[/C][C]-0.302[/C][C]0.307[/C][C]1[/C][/ROW]
[ROW][C]pre:CSWE-pre:C[/C][C]-0.054[/C][C]-0.341[/C][C]0.233[/C][C]1[/C][/ROW]
[ROW][C]post1:WWE-pre:C[/C][C]0.236[/C][C]-0.049[/C][C]0.522[/C][C]0.196[/C][/ROW]
[ROW][C]post2:WWE-pre:C[/C][C]0.109[/C][C]-0.181[/C][C]0.4[/C][C]0.962[/C][/ROW]
[ROW][C]pre:WWE-pre:C[/C][C]-0.008[/C][C]-0.293[/C][C]0.278[/C][C]1[/C][/ROW]
[ROW][C]post2:CSWE-post1:CSWE[/C][C]-0.319[/C][C]-0.621[/C][C]-0.016[/C][C]0.03[/C][/ROW]
[ROW][C]pre:CSWE-post1:CSWE[/C][C]-0.375[/C][C]-0.66[/C][C]-0.09[/C][C]0.002[/C][/ROW]
[ROW][C]post1:WWE-post1:CSWE[/C][C]-0.085[/C][C]-0.368[/C][C]0.199[/C][C]0.991[/C][/ROW]
[ROW][C]post2:WWE-post1:CSWE[/C][C]-0.212[/C][C]-0.501[/C][C]0.077[/C][C]0.352[/C][/ROW]
[ROW][C]pre:WWE-post1:CSWE[/C][C]-0.329[/C][C]-0.612[/C][C]-0.045[/C][C]0.01[/C][/ROW]
[ROW][C]pre:CSWE-post2:CSWE[/C][C]-0.056[/C][C]-0.359[/C][C]0.246[/C][C]1[/C][/ROW]
[ROW][C]post1:WWE-post2:CSWE[/C][C]0.234[/C][C]-0.067[/C][C]0.535[/C][C]0.272[/C][/ROW]
[ROW][C]post2:WWE-post2:CSWE[/C][C]0.107[/C][C]-0.199[/C][C]0.413[/C][C]0.975[/C][/ROW]
[ROW][C]pre:WWE-post2:CSWE[/C][C]-0.01[/C][C]-0.311[/C][C]0.291[/C][C]1[/C][/ROW]
[ROW][C]post1:WWE-pre:CSWE[/C][C]0.29[/C][C]0.007[/C][C]0.574[/C][C]0.04[/C][/ROW]
[ROW][C]post2:WWE-pre:CSWE[/C][C]0.163[/C][C]-0.126[/C][C]0.452[/C][C]0.707[/C][/ROW]
[ROW][C]pre:WWE-pre:CSWE[/C][C]0.046[/C][C]-0.237[/C][C]0.33[/C][C]1[/C][/ROW]
[ROW][C]post2:WWE-post1:WWE[/C][C]-0.127[/C][C]-0.414[/C][C]0.16[/C][C]0.904[/C][/ROW]
[ROW][C]pre:WWE-post1:WWE[/C][C]-0.244[/C][C]-0.526[/C][C]0.038[/C][C]0.151[/C][/ROW]
[ROW][C]pre:WWE-post2:WWE[/C][C]-0.117[/C][C]-0.404[/C][C]0.17[/C][C]0.939[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91073&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91073&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
post2-post1-0.194-0.323-0.0660.001
pre-post1-0.242-0.366-0.1170
pre-post2-0.048-0.1760.0810.658
CSWE-C0.071-0.0570.20.392
WWE-C0.09-0.0360.2160.213
WWE-CSWE0.019-0.1070.1450.934
post2:C-post1:C-0.142-0.4390.1550.858
pre:C-post1:C-0.103-0.3910.1860.973
post1:CSWE-post1:C0.219-0.0680.5060.3
post2:CSWE-post1:C-0.1-0.4040.2040.983
pre:CSWE-post1:C-0.156-0.4430.1310.746
post1:WWE-post1:C0.134-0.1520.4190.871
post2:WWE-post1:C0.007-0.2840.2981
pre:WWE-post1:C-0.11-0.3950.1750.955
pre:C-post2:C0.04-0.2570.3371
post1:CSWE-post2:C0.3610.0650.6560.005
post2:CSWE-post2:C0.042-0.270.3541
pre:CSWE-post2:C-0.014-0.310.2811
post1:WWE-post2:C0.276-0.0180.570.084
post2:WWE-post2:C0.149-0.150.4480.828
pre:WWE-post2:C0.032-0.2620.3261
post1:CSWE-pre:C0.3210.0340.6080.016
post2:CSWE-pre:C0.002-0.3020.3071
pre:CSWE-pre:C-0.054-0.3410.2331
post1:WWE-pre:C0.236-0.0490.5220.196
post2:WWE-pre:C0.109-0.1810.40.962
pre:WWE-pre:C-0.008-0.2930.2781
post2:CSWE-post1:CSWE-0.319-0.621-0.0160.03
pre:CSWE-post1:CSWE-0.375-0.66-0.090.002
post1:WWE-post1:CSWE-0.085-0.3680.1990.991
post2:WWE-post1:CSWE-0.212-0.5010.0770.352
pre:WWE-post1:CSWE-0.329-0.612-0.0450.01
pre:CSWE-post2:CSWE-0.056-0.3590.2461
post1:WWE-post2:CSWE0.234-0.0670.5350.272
post2:WWE-post2:CSWE0.107-0.1990.4130.975
pre:WWE-post2:CSWE-0.01-0.3110.2911
post1:WWE-pre:CSWE0.290.0070.5740.04
post2:WWE-pre:CSWE0.163-0.1260.4520.707
pre:WWE-pre:CSWE0.046-0.2370.331
post2:WWE-post1:WWE-0.127-0.4140.160.904
pre:WWE-post1:WWE-0.244-0.5260.0380.151
pre:WWE-post2:WWE-0.117-0.4040.170.939







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group84.0080
336

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 4.008 & 0 \tabularnewline
  & 336 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91073&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]8[/C][C]4.008[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]336[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91073&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91073&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)
Group84.0080
336



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')