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Description of Statistical Computation

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 05:02:56 -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/t1320746703oeax5b8q1yvocx1.htm/, Retrieved Fri, 26 Apr 2024 11:07:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=140554, Retrieved Fri, 26 Apr 2024 11:07:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Workshop 5 - Task...] [2011-11-03 13:44:48] [fbaf17a8836493f6de0f4e0e997711e1]
- RMPD    [Two-Way ANOVA] [Workshop 5 - Task 6] [2011-11-08 10:02:56] [c897fb90cb9e1f725365d7e541ad7850] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	0	'T'
1	0	'T'
0	1	'T'
0	0	'T'
1	1	'T'
1	1	'T'
1	1	'T'
0	1	'T'
0	1	'T'
1	0	'T'
0	0	'T'
0	1	'T'
0	1	'T'
0	0	'T'
0	NA	'T'
1	1	'T'
1	0	'T'
1	1	'T'
0	1	'T'
0	1	'T'
1	1	'T'
1	0	'T'
0	NA	'T'
1	NA	'T'
1	1	'T'
1	1	'T'
1	NA	'T'
0	NA	'T'
0	0	'T'
1	1	'T'
1	0	'T'
1	0	'T'
0	1	'T'
0	NA	'T'
0	1	'T'
1	NA	'T'
1	0	'T'
0	1	'E'
0	1	'E'
1	1	'E'
1	1	'E'
1	1	'E'
1	0	'E'
1	1	'E'
0	1	'E'
0	1	'E'
0	0	'E'
1	0	'E'
1	1	'E'
0	0	'E'
0	1	'E'
1	1	'E'
0	1	'E'
0	NA	'E'
0	0	'E'
0	1	'E'
0	1	'E'
0	NA	'E'
0	0	'E'
0	NA	'E'
0	1	'E'
1	1	'E'
1	1	'E'
1	1	'E'
0	1	'E'
0	0	'E'
0	1	'E'
0	0	'E'
1	1	'E'
1	1	'E'
0	0	'S'
0	0	'S'
0	0	'S'
0	0	'S'
1	1	'S'
1	1	'S'
0	1	'S'
1	1	'S'
1	1	'S'
1	1	'S'
0	1	'S'
0	1	'S'
0	1	'S'
1	1	'S'
0	NA	'S'
0	1	'S'
1	NA	'S'
1	1	'S'
0	1	'S'
0	NA	'S'
1	0	'S'
1	1	'S'
1	NA	'S'
0	1	'S'
1	1	'S'
1	1	'S'
1	1	'S'
1	1	'S'
0	NA	'S'
0	0	'S'
1	0	'S'
0	1	'S'
0	0	'S'
0	1	'S'
0	0	'S'

Tables (Output of Computation)





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=140554&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=140554&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140554&T=0

As an alternative you can also use a QR Code:  
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
means0.250.25-0.25-0.0280.4170.0990.428-0.4170.012

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 0.25 & 0.25 & -0.25 & -0.028 & 0.417 & 0.099 & 0.428 & -0.417 & 0.012 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140554&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]0.25[/C][C]0.25[/C][C]-0.25[/C][C]-0.028[/C][C]0.417[/C][C]0.099[/C][C]0.428[/C][C]-0.417[/C][C]0.012[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140554&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140554&T=1

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.250.25-0.25-0.0280.4170.0990.428-0.4170.012






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A20.5520.2761.1150.332
Treatment_B20.5520.2761.1140.332
Treatment_A:Treatment_B21.250.3121.2610.291
Residuals9623.7790.248 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 0.552 & 0.276 & 1.115 & 0.332 \tabularnewline
Treatment_B & 2 & 0.552 & 0.276 & 1.114 & 0.332 \tabularnewline
Treatment_A:Treatment_B & 2 & 1.25 & 0.312 & 1.261 & 0.291 \tabularnewline
Residuals & 96 & 23.779 & 0.248 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140554&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]0.552[/C][C]0.276[/C][C]1.115[/C][C]0.332[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]0.552[/C][C]0.276[/C][C]1.114[/C][C]0.332[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]1.25[/C][C]0.312[/C][C]1.261[/C][C]0.291[/C][/ROW]
[ROW][C]Residuals[/C][C]96[/C][C]23.779[/C][C]0.248[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140554&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140554&T=2

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A20.5520.2761.1150.332
Treatment_B20.5520.2761.1140.332
Treatment_A:Treatment_B21.250.3121.2610.291
Residuals9623.7790.248






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.111-0.1560.3780.587
NA-0-0.08-0.4570.2960.867
NA-1-0.191-0.5330.150.38
S-E0.075-0.2130.3620.81
T-E0.174-0.1090.4580.313
T-S0.1-0.180.3790.673
1:E-0:E0.25-0.4020.9020.951
NA:E-0:E-0.25-1.3190.8190.998
0:S-0:E-0.028-0.7950.741
1:S-0:E0.321-0.3350.9780.826
NA:S-0:E0.15-0.751.051
0:T-0:E0.417-0.3041.1380.66
1:T-0:E0.25-0.4210.9210.958
NA:T-0:E0.179-0.6390.9960.999
NA:E-1:E-0.5-1.4720.4720.785
0:S-1:E-0.278-0.9030.3470.891
1:S-1:E0.071-0.410.5531
NA:S-1:E-0.1-0.8830.6831
0:T-1:E0.167-0.40.7340.99
1:T-1:E0-0.5020.5021
NA:T-1:E-0.071-0.7570.6141
0:S-NA:E0.222-0.8311.2750.999
1:S-NA:E0.571-0.4031.5460.642
NA:S-NA:E0.4-0.7541.5540.973
0:T-NA:E0.667-0.3531.6860.496
1:T-NA:E0.5-0.4851.4850.797
NA:T-NA:E0.429-0.6611.5190.943
1:S-0:S0.349-0.280.9790.707
NA:S-0:S0.178-0.7031.0590.999
0:T-0:S0.444-0.2521.1410.53
1:T-0:S0.278-0.3670.9230.907
NA:T-0:S0.206-0.591.0020.996
NA:S-1:S-0.171-0.9570.6150.999
0:T-1:S0.095-0.4760.6671
1:T-1:S-0.071-0.5790.4361
NA:T-1:S-0.143-0.8320.5470.999
0:T-NA:S0.267-0.5741.1070.984
1:T-NA:S0.1-0.6980.8981
NA:T-NA:S0.029-0.8960.9531
1:T-0:T-0.167-0.7550.4220.993
NA:T-0:T-0.238-0.9890.5130.984
NA:T-1:T-0.071-0.7750.6321

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 0.111 & -0.156 & 0.378 & 0.587 \tabularnewline
NA-0 & -0.08 & -0.457 & 0.296 & 0.867 \tabularnewline
NA-1 & -0.191 & -0.533 & 0.15 & 0.38 \tabularnewline
S-E & 0.075 & -0.213 & 0.362 & 0.81 \tabularnewline
T-E & 0.174 & -0.109 & 0.458 & 0.313 \tabularnewline
T-S & 0.1 & -0.18 & 0.379 & 0.673 \tabularnewline
1:E-0:E & 0.25 & -0.402 & 0.902 & 0.951 \tabularnewline
NA:E-0:E & -0.25 & -1.319 & 0.819 & 0.998 \tabularnewline
0:S-0:E & -0.028 & -0.795 & 0.74 & 1 \tabularnewline
1:S-0:E & 0.321 & -0.335 & 0.978 & 0.826 \tabularnewline
NA:S-0:E & 0.15 & -0.75 & 1.05 & 1 \tabularnewline
0:T-0:E & 0.417 & -0.304 & 1.138 & 0.66 \tabularnewline
1:T-0:E & 0.25 & -0.421 & 0.921 & 0.958 \tabularnewline
NA:T-0:E & 0.179 & -0.639 & 0.996 & 0.999 \tabularnewline
NA:E-1:E & -0.5 & -1.472 & 0.472 & 0.785 \tabularnewline
0:S-1:E & -0.278 & -0.903 & 0.347 & 0.891 \tabularnewline
1:S-1:E & 0.071 & -0.41 & 0.553 & 1 \tabularnewline
NA:S-1:E & -0.1 & -0.883 & 0.683 & 1 \tabularnewline
0:T-1:E & 0.167 & -0.4 & 0.734 & 0.99 \tabularnewline
1:T-1:E & 0 & -0.502 & 0.502 & 1 \tabularnewline
NA:T-1:E & -0.071 & -0.757 & 0.614 & 1 \tabularnewline
0:S-NA:E & 0.222 & -0.831 & 1.275 & 0.999 \tabularnewline
1:S-NA:E & 0.571 & -0.403 & 1.546 & 0.642 \tabularnewline
NA:S-NA:E & 0.4 & -0.754 & 1.554 & 0.973 \tabularnewline
0:T-NA:E & 0.667 & -0.353 & 1.686 & 0.496 \tabularnewline
1:T-NA:E & 0.5 & -0.485 & 1.485 & 0.797 \tabularnewline
NA:T-NA:E & 0.429 & -0.661 & 1.519 & 0.943 \tabularnewline
1:S-0:S & 0.349 & -0.28 & 0.979 & 0.707 \tabularnewline
NA:S-0:S & 0.178 & -0.703 & 1.059 & 0.999 \tabularnewline
0:T-0:S & 0.444 & -0.252 & 1.141 & 0.53 \tabularnewline
1:T-0:S & 0.278 & -0.367 & 0.923 & 0.907 \tabularnewline
NA:T-0:S & 0.206 & -0.59 & 1.002 & 0.996 \tabularnewline
NA:S-1:S & -0.171 & -0.957 & 0.615 & 0.999 \tabularnewline
0:T-1:S & 0.095 & -0.476 & 0.667 & 1 \tabularnewline
1:T-1:S & -0.071 & -0.579 & 0.436 & 1 \tabularnewline
NA:T-1:S & -0.143 & -0.832 & 0.547 & 0.999 \tabularnewline
0:T-NA:S & 0.267 & -0.574 & 1.107 & 0.984 \tabularnewline
1:T-NA:S & 0.1 & -0.698 & 0.898 & 1 \tabularnewline
NA:T-NA:S & 0.029 & -0.896 & 0.953 & 1 \tabularnewline
1:T-0:T & -0.167 & -0.755 & 0.422 & 0.993 \tabularnewline
NA:T-0:T & -0.238 & -0.989 & 0.513 & 0.984 \tabularnewline
NA:T-1:T & -0.071 & -0.775 & 0.632 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140554&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]1-0[/C][C]0.111[/C][C]-0.156[/C][C]0.378[/C][C]0.587[/C][/ROW]
[ROW][C]NA-0[/C][C]-0.08[/C][C]-0.457[/C][C]0.296[/C][C]0.867[/C][/ROW]
[ROW][C]NA-1[/C][C]-0.191[/C][C]-0.533[/C][C]0.15[/C][C]0.38[/C][/ROW]
[ROW][C]S-E[/C][C]0.075[/C][C]-0.213[/C][C]0.362[/C][C]0.81[/C][/ROW]
[ROW][C]T-E[/C][C]0.174[/C][C]-0.109[/C][C]0.458[/C][C]0.313[/C][/ROW]
[ROW][C]T-S[/C][C]0.1[/C][C]-0.18[/C][C]0.379[/C][C]0.673[/C][/ROW]
[ROW][C]1:E-0:E[/C][C]0.25[/C][C]-0.402[/C][C]0.902[/C][C]0.951[/C][/ROW]
[ROW][C]NA:E-0:E[/C][C]-0.25[/C][C]-1.319[/C][C]0.819[/C][C]0.998[/C][/ROW]
[ROW][C]0:S-0:E[/C][C]-0.028[/C][C]-0.795[/C][C]0.74[/C][C]1[/C][/ROW]
[ROW][C]1:S-0:E[/C][C]0.321[/C][C]-0.335[/C][C]0.978[/C][C]0.826[/C][/ROW]
[ROW][C]NA:S-0:E[/C][C]0.15[/C][C]-0.75[/C][C]1.05[/C][C]1[/C][/ROW]
[ROW][C]0:T-0:E[/C][C]0.417[/C][C]-0.304[/C][C]1.138[/C][C]0.66[/C][/ROW]
[ROW][C]1:T-0:E[/C][C]0.25[/C][C]-0.421[/C][C]0.921[/C][C]0.958[/C][/ROW]
[ROW][C]NA:T-0:E[/C][C]0.179[/C][C]-0.639[/C][C]0.996[/C][C]0.999[/C][/ROW]
[ROW][C]NA:E-1:E[/C][C]-0.5[/C][C]-1.472[/C][C]0.472[/C][C]0.785[/C][/ROW]
[ROW][C]0:S-1:E[/C][C]-0.278[/C][C]-0.903[/C][C]0.347[/C][C]0.891[/C][/ROW]
[ROW][C]1:S-1:E[/C][C]0.071[/C][C]-0.41[/C][C]0.553[/C][C]1[/C][/ROW]
[ROW][C]NA:S-1:E[/C][C]-0.1[/C][C]-0.883[/C][C]0.683[/C][C]1[/C][/ROW]
[ROW][C]0:T-1:E[/C][C]0.167[/C][C]-0.4[/C][C]0.734[/C][C]0.99[/C][/ROW]
[ROW][C]1:T-1:E[/C][C]0[/C][C]-0.502[/C][C]0.502[/C][C]1[/C][/ROW]
[ROW][C]NA:T-1:E[/C][C]-0.071[/C][C]-0.757[/C][C]0.614[/C][C]1[/C][/ROW]
[ROW][C]0:S-NA:E[/C][C]0.222[/C][C]-0.831[/C][C]1.275[/C][C]0.999[/C][/ROW]
[ROW][C]1:S-NA:E[/C][C]0.571[/C][C]-0.403[/C][C]1.546[/C][C]0.642[/C][/ROW]
[ROW][C]NA:S-NA:E[/C][C]0.4[/C][C]-0.754[/C][C]1.554[/C][C]0.973[/C][/ROW]
[ROW][C]0:T-NA:E[/C][C]0.667[/C][C]-0.353[/C][C]1.686[/C][C]0.496[/C][/ROW]
[ROW][C]1:T-NA:E[/C][C]0.5[/C][C]-0.485[/C][C]1.485[/C][C]0.797[/C][/ROW]
[ROW][C]NA:T-NA:E[/C][C]0.429[/C][C]-0.661[/C][C]1.519[/C][C]0.943[/C][/ROW]
[ROW][C]1:S-0:S[/C][C]0.349[/C][C]-0.28[/C][C]0.979[/C][C]0.707[/C][/ROW]
[ROW][C]NA:S-0:S[/C][C]0.178[/C][C]-0.703[/C][C]1.059[/C][C]0.999[/C][/ROW]
[ROW][C]0:T-0:S[/C][C]0.444[/C][C]-0.252[/C][C]1.141[/C][C]0.53[/C][/ROW]
[ROW][C]1:T-0:S[/C][C]0.278[/C][C]-0.367[/C][C]0.923[/C][C]0.907[/C][/ROW]
[ROW][C]NA:T-0:S[/C][C]0.206[/C][C]-0.59[/C][C]1.002[/C][C]0.996[/C][/ROW]
[ROW][C]NA:S-1:S[/C][C]-0.171[/C][C]-0.957[/C][C]0.615[/C][C]0.999[/C][/ROW]
[ROW][C]0:T-1:S[/C][C]0.095[/C][C]-0.476[/C][C]0.667[/C][C]1[/C][/ROW]
[ROW][C]1:T-1:S[/C][C]-0.071[/C][C]-0.579[/C][C]0.436[/C][C]1[/C][/ROW]
[ROW][C]NA:T-1:S[/C][C]-0.143[/C][C]-0.832[/C][C]0.547[/C][C]0.999[/C][/ROW]
[ROW][C]0:T-NA:S[/C][C]0.267[/C][C]-0.574[/C][C]1.107[/C][C]0.984[/C][/ROW]
[ROW][C]1:T-NA:S[/C][C]0.1[/C][C]-0.698[/C][C]0.898[/C][C]1[/C][/ROW]
[ROW][C]NA:T-NA:S[/C][C]0.029[/C][C]-0.896[/C][C]0.953[/C][C]1[/C][/ROW]
[ROW][C]1:T-0:T[/C][C]-0.167[/C][C]-0.755[/C][C]0.422[/C][C]0.993[/C][/ROW]
[ROW][C]NA:T-0:T[/C][C]-0.238[/C][C]-0.989[/C][C]0.513[/C][C]0.984[/C][/ROW]
[ROW][C]NA:T-1:T[/C][C]-0.071[/C][C]-0.775[/C][C]0.632[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140554&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140554&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.111-0.1560.3780.587
NA-0-0.08-0.4570.2960.867
NA-1-0.191-0.5330.150.38
S-E0.075-0.2130.3620.81
T-E0.174-0.1090.4580.313
T-S0.1-0.180.3790.673
1:E-0:E0.25-0.4020.9020.951
NA:E-0:E-0.25-1.3190.8190.998
0:S-0:E-0.028-0.7950.741
1:S-0:E0.321-0.3350.9780.826
NA:S-0:E0.15-0.751.051
0:T-0:E0.417-0.3041.1380.66
1:T-0:E0.25-0.4210.9210.958
NA:T-0:E0.179-0.6390.9960.999
NA:E-1:E-0.5-1.4720.4720.785
0:S-1:E-0.278-0.9030.3470.891
1:S-1:E0.071-0.410.5531
NA:S-1:E-0.1-0.8830.6831
0:T-1:E0.167-0.40.7340.99
1:T-1:E0-0.5020.5021
NA:T-1:E-0.071-0.7570.6141
0:S-NA:E0.222-0.8311.2750.999
1:S-NA:E0.571-0.4031.5460.642
NA:S-NA:E0.4-0.7541.5540.973
0:T-NA:E0.667-0.3531.6860.496
1:T-NA:E0.5-0.4851.4850.797
NA:T-NA:E0.429-0.6611.5190.943
1:S-0:S0.349-0.280.9790.707
NA:S-0:S0.178-0.7031.0590.999
0:T-0:S0.444-0.2521.1410.53
1:T-0:S0.278-0.3670.9230.907
NA:T-0:S0.206-0.591.0020.996
NA:S-1:S-0.171-0.9570.6150.999
0:T-1:S0.095-0.4760.6671
1:T-1:S-0.071-0.5790.4361
NA:T-1:S-0.143-0.8320.5470.999
0:T-NA:S0.267-0.5741.1070.984
1:T-NA:S0.1-0.6980.8981
NA:T-NA:S0.029-0.8960.9531
1:T-0:T-0.167-0.7550.4220.993
NA:T-0:T-0.238-0.9890.5130.984
NA:T-1:T-0.071-0.7750.6321






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group81.2370.286
96 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 1.237 & 0.286 \tabularnewline
  & 96 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=140554&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]1.237[/C][C]0.286[/C][/ROW]
[ROW][C] [/C][C]96[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=140554&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=140554&T=4

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group81.2370.286
96


Figures (Output of Computation)

Input Parameters & R Code

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')