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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 computationThu, 07 Jun 2012 10:41:15 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jun/07/t1339080144e36vbs113607ujx.htm/, Retrieved Sat, 04 May 2024 15:33:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168735, Retrieved Sat, 04 May 2024 15:33:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact222
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [two way anova] [2012-06-07 14:41:15] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
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Dataseries X:
52	'A'	'1C'
53	'A'	'1C'
54	'A'	'1C'
57	'A'	'1C'
60	'A'	'1C'
60	'A'	'1C'
60	'A'	'1C'
62	'A'	'1C'
64	'A'	'1C'
66	'A'	'1C'
56	'B'	'1C'
57	'B'	'1C'
58	'B'	'1C'
59	'B'	'1C'
59	'B'	'1C'
60	'B'	'1C'
60	'B'	'1C'
66	'B'	'1C'
66	'B'	'1C'
71	'B'	'1C'
54	'C'	'1C'
58	'C'	'1C'
58	'C'	'1C'
59	'C'	'1C'
60	'C'	'1C'
61	'C'	'1C'
62	'C'	'1C'
65	'C'	'1C'
68	'C'	'1C'
69	'C'	'1C'
43	'A'	'2C'
45	'A'	'2C'
47	'A'	'2C'
49	'A'	'2C'
49	'A'	'2C'
50	'A'	'2C'
50	'A'	'2C'
52	'A'	'2C'
56	'A'	'2C'
58	'A'	'2C'
43	'B'	'2C'
46	'B'	'2C'
48	'B'	'2C'
49	'B'	'2C'
50	'B'	'2C'
50	'B'	'2C'
51	'B'	'2C'
54	'B'	'2C'
56	'B'	'2C'
58	'B'	'2C'
44	'C'	'2C'
47	'C'	'2C'
48	'C'	'2C'
49	'C'	'2C'
50	'C'	'2C'
50	'C'	'2C'
52	'C'	'2C'
55	'C'	'2C'
56	'C'	'2C'
60	'C'	'2C'
39	'A'	'2Crt'
42	'A'	'2Crt'
42	'A'	'2Crt'
45	'A'	'2Crt'
46	'A'	'2Crt'
47	'A'	'2Crt'
47	'A'	'2Crt'
49	'A'	'2Crt'
52	'A'	'2Crt'
55	'A'	'2Crt'
40	'B'	'2Crt'
42	'B'	'2Crt'
44	'B'	'2Crt'
45	'B'	'2Crt'
46	'B'	'2Crt'
47	'B'	'2Crt'
48	'B'	'2Crt'
49	'B'	'2Crt'
52	'B'	'2Crt'
57	'B'	'2Crt'
42	'C'	'2Crt'
42	'C'	'2Crt'
44	'C'	'2Crt'
45	'C'	'2Crt'
46	'C'	'2Crt'
47	'C'	'2Crt'
48	'C'	'2Crt'
49	'C'	'2Crt'
54	'C'	'2Crt'
60	'C'	'2Crt'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168735&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168735&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168735&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'Gertrude Mary Cox' @ cox.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means58.82.42.6-8.9-12.4-1.8-1.4-1.8-1.3

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 58.8 & 2.4 & 2.6 & -8.9 & -12.4 & -1.8 & -1.4 & -1.8 & -1.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168735&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]58.8[/C][C]2.4[/C][C]2.6[/C][C]-8.9[/C][C]-12.4[/C][C]-1.8[/C][C]-1.4[/C][C]-1.8[/C][C]-1.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168735&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168735&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
means58.82.42.6-8.9-12.4-1.8-1.4-1.8-1.3







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A245.822.90.9790.38
Treatment_B22918.0671459.03362.3850
Treatment_A:Treatment_B211.7332.9330.1250.973
Residuals811894.423.388

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 45.8 & 22.9 & 0.979 & 0.38 \tabularnewline
Treatment_B & 2 & 2918.067 & 1459.033 & 62.385 & 0 \tabularnewline
Treatment_A:Treatment_B & 2 & 11.733 & 2.933 & 0.125 & 0.973 \tabularnewline
Residuals & 81 & 1894.4 & 23.388 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168735&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]45.8[/C][C]22.9[/C][C]0.979[/C][C]0.38[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]2918.067[/C][C]1459.033[/C][C]62.385[/C][C]0[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]11.733[/C][C]2.933[/C][C]0.125[/C][C]0.973[/C][/ROW]
[ROW][C]Residuals[/C][C]81[/C][C]1894.4[/C][C]23.388[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168735&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168735&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_A245.822.90.9790.38
Treatment_B22918.0671459.03362.3850
Treatment_A:Treatment_B211.7332.9330.1250.973
Residuals811894.423.388







Tukey Honest Significant Difference Comparisons
difflwruprp adj
B-A1.2-1.7814.1810.603
C-A1.7-1.2814.6810.366
C-B0.5-2.4813.4810.916
2C-1C-9.967-12.948-6.9850
2Crt-1C-13.433-16.415-10.4520
2Crt-2C-3.467-6.448-0.4850.019
B:1C-A:1C2.4-4.4939.2930.971
C:1C-A:1C2.6-4.2939.4930.954
A:2C-A:1C-8.9-15.793-2.0070.003
B:2C-A:1C-8.3-15.193-1.4070.007
C:2C-A:1C-7.7-14.593-0.8070.017
A:2Crt-A:1C-12.4-19.293-5.5070
B:2Crt-A:1C-11.8-18.693-4.9070
C:2Crt-A:1C-11.1-17.993-4.2070
C:1C-B:1C0.2-6.6937.0931
A:2C-B:1C-11.3-18.193-4.4070
B:2C-B:1C-10.7-17.593-3.8070
C:2C-B:1C-10.1-16.993-3.2070
A:2Crt-B:1C-14.8-21.693-7.9070
B:2Crt-B:1C-14.2-21.093-7.3070
C:2Crt-B:1C-13.5-20.393-6.6070
A:2C-C:1C-11.5-18.393-4.6070
B:2C-C:1C-10.9-17.793-4.0070
C:2C-C:1C-10.3-17.193-3.4070
A:2Crt-C:1C-15-21.893-8.1070
B:2Crt-C:1C-14.4-21.293-7.5070
C:2Crt-C:1C-13.7-20.593-6.8070
B:2C-A:2C0.6-6.2937.4931
C:2C-A:2C1.2-5.6938.0931
A:2Crt-A:2C-3.5-10.3933.3930.792
B:2Crt-A:2C-2.9-9.7933.9930.916
C:2Crt-A:2C-2.2-9.0934.6930.983
C:2C-B:2C0.6-6.2937.4931
A:2Crt-B:2C-4.1-10.9932.7930.619
B:2Crt-B:2C-3.5-10.3933.3930.792
C:2Crt-B:2C-2.8-9.6934.0930.93
A:2Crt-C:2C-4.7-11.5932.1930.433
B:2Crt-C:2C-4.1-10.9932.7930.619
C:2Crt-C:2C-3.4-10.2933.4930.817
B:2Crt-A:2Crt0.6-6.2937.4931
C:2Crt-A:2Crt1.3-5.5938.1931
C:2Crt-B:2Crt0.7-6.1937.5931

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
B-A & 1.2 & -1.781 & 4.181 & 0.603 \tabularnewline
C-A & 1.7 & -1.281 & 4.681 & 0.366 \tabularnewline
C-B & 0.5 & -2.481 & 3.481 & 0.916 \tabularnewline
2C-1C & -9.967 & -12.948 & -6.985 & 0 \tabularnewline
2Crt-1C & -13.433 & -16.415 & -10.452 & 0 \tabularnewline
2Crt-2C & -3.467 & -6.448 & -0.485 & 0.019 \tabularnewline
B:1C-A:1C & 2.4 & -4.493 & 9.293 & 0.971 \tabularnewline
C:1C-A:1C & 2.6 & -4.293 & 9.493 & 0.954 \tabularnewline
A:2C-A:1C & -8.9 & -15.793 & -2.007 & 0.003 \tabularnewline
B:2C-A:1C & -8.3 & -15.193 & -1.407 & 0.007 \tabularnewline
C:2C-A:1C & -7.7 & -14.593 & -0.807 & 0.017 \tabularnewline
A:2Crt-A:1C & -12.4 & -19.293 & -5.507 & 0 \tabularnewline
B:2Crt-A:1C & -11.8 & -18.693 & -4.907 & 0 \tabularnewline
C:2Crt-A:1C & -11.1 & -17.993 & -4.207 & 0 \tabularnewline
C:1C-B:1C & 0.2 & -6.693 & 7.093 & 1 \tabularnewline
A:2C-B:1C & -11.3 & -18.193 & -4.407 & 0 \tabularnewline
B:2C-B:1C & -10.7 & -17.593 & -3.807 & 0 \tabularnewline
C:2C-B:1C & -10.1 & -16.993 & -3.207 & 0 \tabularnewline
A:2Crt-B:1C & -14.8 & -21.693 & -7.907 & 0 \tabularnewline
B:2Crt-B:1C & -14.2 & -21.093 & -7.307 & 0 \tabularnewline
C:2Crt-B:1C & -13.5 & -20.393 & -6.607 & 0 \tabularnewline
A:2C-C:1C & -11.5 & -18.393 & -4.607 & 0 \tabularnewline
B:2C-C:1C & -10.9 & -17.793 & -4.007 & 0 \tabularnewline
C:2C-C:1C & -10.3 & -17.193 & -3.407 & 0 \tabularnewline
A:2Crt-C:1C & -15 & -21.893 & -8.107 & 0 \tabularnewline
B:2Crt-C:1C & -14.4 & -21.293 & -7.507 & 0 \tabularnewline
C:2Crt-C:1C & -13.7 & -20.593 & -6.807 & 0 \tabularnewline
B:2C-A:2C & 0.6 & -6.293 & 7.493 & 1 \tabularnewline
C:2C-A:2C & 1.2 & -5.693 & 8.093 & 1 \tabularnewline
A:2Crt-A:2C & -3.5 & -10.393 & 3.393 & 0.792 \tabularnewline
B:2Crt-A:2C & -2.9 & -9.793 & 3.993 & 0.916 \tabularnewline
C:2Crt-A:2C & -2.2 & -9.093 & 4.693 & 0.983 \tabularnewline
C:2C-B:2C & 0.6 & -6.293 & 7.493 & 1 \tabularnewline
A:2Crt-B:2C & -4.1 & -10.993 & 2.793 & 0.619 \tabularnewline
B:2Crt-B:2C & -3.5 & -10.393 & 3.393 & 0.792 \tabularnewline
C:2Crt-B:2C & -2.8 & -9.693 & 4.093 & 0.93 \tabularnewline
A:2Crt-C:2C & -4.7 & -11.593 & 2.193 & 0.433 \tabularnewline
B:2Crt-C:2C & -4.1 & -10.993 & 2.793 & 0.619 \tabularnewline
C:2Crt-C:2C & -3.4 & -10.293 & 3.493 & 0.817 \tabularnewline
B:2Crt-A:2Crt & 0.6 & -6.293 & 7.493 & 1 \tabularnewline
C:2Crt-A:2Crt & 1.3 & -5.593 & 8.193 & 1 \tabularnewline
C:2Crt-B:2Crt & 0.7 & -6.193 & 7.593 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168735&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]B-A[/C][C]1.2[/C][C]-1.781[/C][C]4.181[/C][C]0.603[/C][/ROW]
[ROW][C]C-A[/C][C]1.7[/C][C]-1.281[/C][C]4.681[/C][C]0.366[/C][/ROW]
[ROW][C]C-B[/C][C]0.5[/C][C]-2.481[/C][C]3.481[/C][C]0.916[/C][/ROW]
[ROW][C]2C-1C[/C][C]-9.967[/C][C]-12.948[/C][C]-6.985[/C][C]0[/C][/ROW]
[ROW][C]2Crt-1C[/C][C]-13.433[/C][C]-16.415[/C][C]-10.452[/C][C]0[/C][/ROW]
[ROW][C]2Crt-2C[/C][C]-3.467[/C][C]-6.448[/C][C]-0.485[/C][C]0.019[/C][/ROW]
[ROW][C]B:1C-A:1C[/C][C]2.4[/C][C]-4.493[/C][C]9.293[/C][C]0.971[/C][/ROW]
[ROW][C]C:1C-A:1C[/C][C]2.6[/C][C]-4.293[/C][C]9.493[/C][C]0.954[/C][/ROW]
[ROW][C]A:2C-A:1C[/C][C]-8.9[/C][C]-15.793[/C][C]-2.007[/C][C]0.003[/C][/ROW]
[ROW][C]B:2C-A:1C[/C][C]-8.3[/C][C]-15.193[/C][C]-1.407[/C][C]0.007[/C][/ROW]
[ROW][C]C:2C-A:1C[/C][C]-7.7[/C][C]-14.593[/C][C]-0.807[/C][C]0.017[/C][/ROW]
[ROW][C]A:2Crt-A:1C[/C][C]-12.4[/C][C]-19.293[/C][C]-5.507[/C][C]0[/C][/ROW]
[ROW][C]B:2Crt-A:1C[/C][C]-11.8[/C][C]-18.693[/C][C]-4.907[/C][C]0[/C][/ROW]
[ROW][C]C:2Crt-A:1C[/C][C]-11.1[/C][C]-17.993[/C][C]-4.207[/C][C]0[/C][/ROW]
[ROW][C]C:1C-B:1C[/C][C]0.2[/C][C]-6.693[/C][C]7.093[/C][C]1[/C][/ROW]
[ROW][C]A:2C-B:1C[/C][C]-11.3[/C][C]-18.193[/C][C]-4.407[/C][C]0[/C][/ROW]
[ROW][C]B:2C-B:1C[/C][C]-10.7[/C][C]-17.593[/C][C]-3.807[/C][C]0[/C][/ROW]
[ROW][C]C:2C-B:1C[/C][C]-10.1[/C][C]-16.993[/C][C]-3.207[/C][C]0[/C][/ROW]
[ROW][C]A:2Crt-B:1C[/C][C]-14.8[/C][C]-21.693[/C][C]-7.907[/C][C]0[/C][/ROW]
[ROW][C]B:2Crt-B:1C[/C][C]-14.2[/C][C]-21.093[/C][C]-7.307[/C][C]0[/C][/ROW]
[ROW][C]C:2Crt-B:1C[/C][C]-13.5[/C][C]-20.393[/C][C]-6.607[/C][C]0[/C][/ROW]
[ROW][C]A:2C-C:1C[/C][C]-11.5[/C][C]-18.393[/C][C]-4.607[/C][C]0[/C][/ROW]
[ROW][C]B:2C-C:1C[/C][C]-10.9[/C][C]-17.793[/C][C]-4.007[/C][C]0[/C][/ROW]
[ROW][C]C:2C-C:1C[/C][C]-10.3[/C][C]-17.193[/C][C]-3.407[/C][C]0[/C][/ROW]
[ROW][C]A:2Crt-C:1C[/C][C]-15[/C][C]-21.893[/C][C]-8.107[/C][C]0[/C][/ROW]
[ROW][C]B:2Crt-C:1C[/C][C]-14.4[/C][C]-21.293[/C][C]-7.507[/C][C]0[/C][/ROW]
[ROW][C]C:2Crt-C:1C[/C][C]-13.7[/C][C]-20.593[/C][C]-6.807[/C][C]0[/C][/ROW]
[ROW][C]B:2C-A:2C[/C][C]0.6[/C][C]-6.293[/C][C]7.493[/C][C]1[/C][/ROW]
[ROW][C]C:2C-A:2C[/C][C]1.2[/C][C]-5.693[/C][C]8.093[/C][C]1[/C][/ROW]
[ROW][C]A:2Crt-A:2C[/C][C]-3.5[/C][C]-10.393[/C][C]3.393[/C][C]0.792[/C][/ROW]
[ROW][C]B:2Crt-A:2C[/C][C]-2.9[/C][C]-9.793[/C][C]3.993[/C][C]0.916[/C][/ROW]
[ROW][C]C:2Crt-A:2C[/C][C]-2.2[/C][C]-9.093[/C][C]4.693[/C][C]0.983[/C][/ROW]
[ROW][C]C:2C-B:2C[/C][C]0.6[/C][C]-6.293[/C][C]7.493[/C][C]1[/C][/ROW]
[ROW][C]A:2Crt-B:2C[/C][C]-4.1[/C][C]-10.993[/C][C]2.793[/C][C]0.619[/C][/ROW]
[ROW][C]B:2Crt-B:2C[/C][C]-3.5[/C][C]-10.393[/C][C]3.393[/C][C]0.792[/C][/ROW]
[ROW][C]C:2Crt-B:2C[/C][C]-2.8[/C][C]-9.693[/C][C]4.093[/C][C]0.93[/C][/ROW]
[ROW][C]A:2Crt-C:2C[/C][C]-4.7[/C][C]-11.593[/C][C]2.193[/C][C]0.433[/C][/ROW]
[ROW][C]B:2Crt-C:2C[/C][C]-4.1[/C][C]-10.993[/C][C]2.793[/C][C]0.619[/C][/ROW]
[ROW][C]C:2Crt-C:2C[/C][C]-3.4[/C][C]-10.293[/C][C]3.493[/C][C]0.817[/C][/ROW]
[ROW][C]B:2Crt-A:2Crt[/C][C]0.6[/C][C]-6.293[/C][C]7.493[/C][C]1[/C][/ROW]
[ROW][C]C:2Crt-A:2Crt[/C][C]1.3[/C][C]-5.593[/C][C]8.193[/C][C]1[/C][/ROW]
[ROW][C]C:2Crt-B:2Crt[/C][C]0.7[/C][C]-6.193[/C][C]7.593[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168735&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168735&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
B-A1.2-1.7814.1810.603
C-A1.7-1.2814.6810.366
C-B0.5-2.4813.4810.916
2C-1C-9.967-12.948-6.9850
2Crt-1C-13.433-16.415-10.4520
2Crt-2C-3.467-6.448-0.4850.019
B:1C-A:1C2.4-4.4939.2930.971
C:1C-A:1C2.6-4.2939.4930.954
A:2C-A:1C-8.9-15.793-2.0070.003
B:2C-A:1C-8.3-15.193-1.4070.007
C:2C-A:1C-7.7-14.593-0.8070.017
A:2Crt-A:1C-12.4-19.293-5.5070
B:2Crt-A:1C-11.8-18.693-4.9070
C:2Crt-A:1C-11.1-17.993-4.2070
C:1C-B:1C0.2-6.6937.0931
A:2C-B:1C-11.3-18.193-4.4070
B:2C-B:1C-10.7-17.593-3.8070
C:2C-B:1C-10.1-16.993-3.2070
A:2Crt-B:1C-14.8-21.693-7.9070
B:2Crt-B:1C-14.2-21.093-7.3070
C:2Crt-B:1C-13.5-20.393-6.6070
A:2C-C:1C-11.5-18.393-4.6070
B:2C-C:1C-10.9-17.793-4.0070
C:2C-C:1C-10.3-17.193-3.4070
A:2Crt-C:1C-15-21.893-8.1070
B:2Crt-C:1C-14.4-21.293-7.5070
C:2Crt-C:1C-13.7-20.593-6.8070
B:2C-A:2C0.6-6.2937.4931
C:2C-A:2C1.2-5.6938.0931
A:2Crt-A:2C-3.5-10.3933.3930.792
B:2Crt-A:2C-2.9-9.7933.9930.916
C:2Crt-A:2C-2.2-9.0934.6930.983
C:2C-B:2C0.6-6.2937.4931
A:2Crt-B:2C-4.1-10.9932.7930.619
B:2Crt-B:2C-3.5-10.3933.3930.792
C:2Crt-B:2C-2.8-9.6934.0930.93
A:2Crt-C:2C-4.7-11.5932.1930.433
B:2Crt-C:2C-4.1-10.9932.7930.619
C:2Crt-C:2C-3.4-10.2933.4930.817
B:2Crt-A:2Crt0.6-6.2937.4931
C:2Crt-A:2Crt1.3-5.5938.1931
C:2Crt-B:2Crt0.7-6.1937.5931







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group80.0331
81

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 0.033 & 1 \tabularnewline
  & 81 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168735&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]0.033[/C][C]1[/C][/ROW]
[ROW][C] [/C][C]81[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168735&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168735&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)
Group80.0331
81



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')