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Author's title

Author*Unverified author*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationTue, 03 Jul 2012 14:50:43 -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/Jul/03/t1341341681igotz7a69jo6y4k.htm/, Retrieved Sat, 27 Apr 2024 05:58:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168762, Retrieved Sat, 27 Apr 2024 05:58:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact202
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [cadmium] [2012-07-03 18:50:43] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
49.4 'SM'	'M'
63.9	'SM'	'M'
97.4	'Mo'	'M'
27.3	'Mo'	'M'
25.0	'Rq'	'M'
30.5	'Rq'	'M'
37.1	'SM'	'C'
31.1	'SM'	'C'
38.7	'Mo'	'C'
18.8	'Mo'	'C'
14.5	'Rq'	'C'
21.8	'Rq'	'C'
40.2	'SM'	'0'
37.9	'SM'	'0'
45.9	'Mo'	'0'
55.4	'Mo'	'0'
14.1	'Rq'	'0'
15.0	'Rq'	'0'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168762&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168762&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168762&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means50.65-36.1-11.6-21.911.725.516.951.55.9

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 50.65 & -36.1 & -11.6 & -21.9 & 11.7 & 25.5 & 16.95 & 1.5 & 5.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168762&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]50.65[/C][C]-36.1[/C][C]-11.6[/C][C]-21.9[/C][C]11.7[/C][C]25.5[/C][C]16.95[/C][C]1.5[/C][C]5.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168762&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168762&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
means50.65-36.1-11.6-21.911.725.516.951.55.9







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A22569.3141284.6574.0310.056
Treatment_B21482.194741.0972.3260.153
Treatment_A:Treatment_B2429.529107.3820.3370.846
Residuals92868.08318.676

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 2569.314 & 1284.657 & 4.031 & 0.056 \tabularnewline
Treatment_B & 2 & 1482.194 & 741.097 & 2.326 & 0.153 \tabularnewline
Treatment_A:Treatment_B & 2 & 429.529 & 107.382 & 0.337 & 0.846 \tabularnewline
Residuals & 9 & 2868.08 & 318.676 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168762&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]2569.314[/C][C]1284.657[/C][C]4.031[/C][C]0.056[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]1482.194[/C][C]741.097[/C][C]2.326[/C][C]0.153[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]429.529[/C][C]107.382[/C][C]0.337[/C][C]0.846[/C][/ROW]
[ROW][C]Residuals[/C][C]9[/C][C]2868.08[/C][C]318.676[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168762&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168762&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_A22569.3141284.6574.0310.056
Treatment_B21482.194741.0972.3260.153
Treatment_A:Treatment_B2429.529107.3820.3370.846
Residuals92868.08318.676







Tukey Honest Significant Difference Comparisons
difflwruprp adj
Rq-Mo-27.1-55.8761.6760.064
SM-Mo-3.983-32.75924.7930.922
SM-Rq23.117-5.65951.8930.117
C-0-7.75-36.52621.0260.74
M-014.167-14.60942.9430.393
M-C21.917-6.85950.6930.139
Rq:0-Mo:0-36.1-106.72234.5220.564
SM:0-Mo:0-11.6-82.22259.0220.998
Mo:C-Mo:0-21.9-92.52248.7220.93
Rq:C-Mo:0-32.5-103.12238.1220.672
SM:C-Mo:0-16.55-87.17254.0720.985
Mo:M-Mo:011.7-58.92282.3220.998
Rq:M-Mo:0-22.9-93.52247.7220.914
SM:M-Mo:06-64.62276.6221
SM:0-Rq:024.5-46.12295.1220.883
Mo:C-Rq:014.2-56.42284.8220.994
Rq:C-Rq:03.6-67.02274.2221
SM:C-Rq:019.55-51.07290.1720.961
Mo:M-Rq:047.8-22.822118.4220.273
Rq:M-Rq:013.2-57.42283.8220.996
SM:M-Rq:042.1-28.522112.7220.399
Mo:C-SM:0-10.3-80.92260.3220.999
Rq:C-SM:0-20.9-91.52249.7220.945
SM:C-SM:0-4.95-75.57265.6721
Mo:M-SM:023.3-47.32293.9220.907
Rq:M-SM:0-11.3-81.92259.3220.999
SM:M-SM:017.6-53.02288.2220.978
Rq:C-Mo:C-10.6-81.22260.0220.999
SM:C-Mo:C5.35-65.27275.9721
Mo:M-Mo:C33.6-37.022104.2220.639
Rq:M-Mo:C-1-71.62269.6221
SM:M-Mo:C27.9-42.72298.5220.803
SM:C-Rq:C15.95-54.67286.5720.988
Mo:M-Rq:C44.2-26.422114.8220.349
Rq:M-Rq:C9.6-61.02280.2221
SM:M-Rq:C38.5-32.122109.1220.495
Mo:M-SM:C28.25-42.37298.8720.794
Rq:M-SM:C-6.35-76.97264.2721
SM:M-SM:C22.55-48.07293.1720.92
Rq:M-Mo:M-34.6-105.22236.0220.609
SM:M-Mo:M-5.7-76.32264.9221
SM:M-Rq:M28.9-41.72299.5220.776

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
Rq-Mo & -27.1 & -55.876 & 1.676 & 0.064 \tabularnewline
SM-Mo & -3.983 & -32.759 & 24.793 & 0.922 \tabularnewline
SM-Rq & 23.117 & -5.659 & 51.893 & 0.117 \tabularnewline
C-0 & -7.75 & -36.526 & 21.026 & 0.74 \tabularnewline
M-0 & 14.167 & -14.609 & 42.943 & 0.393 \tabularnewline
M-C & 21.917 & -6.859 & 50.693 & 0.139 \tabularnewline
Rq:0-Mo:0 & -36.1 & -106.722 & 34.522 & 0.564 \tabularnewline
SM:0-Mo:0 & -11.6 & -82.222 & 59.022 & 0.998 \tabularnewline
Mo:C-Mo:0 & -21.9 & -92.522 & 48.722 & 0.93 \tabularnewline
Rq:C-Mo:0 & -32.5 & -103.122 & 38.122 & 0.672 \tabularnewline
SM:C-Mo:0 & -16.55 & -87.172 & 54.072 & 0.985 \tabularnewline
Mo:M-Mo:0 & 11.7 & -58.922 & 82.322 & 0.998 \tabularnewline
Rq:M-Mo:0 & -22.9 & -93.522 & 47.722 & 0.914 \tabularnewline
SM:M-Mo:0 & 6 & -64.622 & 76.622 & 1 \tabularnewline
SM:0-Rq:0 & 24.5 & -46.122 & 95.122 & 0.883 \tabularnewline
Mo:C-Rq:0 & 14.2 & -56.422 & 84.822 & 0.994 \tabularnewline
Rq:C-Rq:0 & 3.6 & -67.022 & 74.222 & 1 \tabularnewline
SM:C-Rq:0 & 19.55 & -51.072 & 90.172 & 0.961 \tabularnewline
Mo:M-Rq:0 & 47.8 & -22.822 & 118.422 & 0.273 \tabularnewline
Rq:M-Rq:0 & 13.2 & -57.422 & 83.822 & 0.996 \tabularnewline
SM:M-Rq:0 & 42.1 & -28.522 & 112.722 & 0.399 \tabularnewline
Mo:C-SM:0 & -10.3 & -80.922 & 60.322 & 0.999 \tabularnewline
Rq:C-SM:0 & -20.9 & -91.522 & 49.722 & 0.945 \tabularnewline
SM:C-SM:0 & -4.95 & -75.572 & 65.672 & 1 \tabularnewline
Mo:M-SM:0 & 23.3 & -47.322 & 93.922 & 0.907 \tabularnewline
Rq:M-SM:0 & -11.3 & -81.922 & 59.322 & 0.999 \tabularnewline
SM:M-SM:0 & 17.6 & -53.022 & 88.222 & 0.978 \tabularnewline
Rq:C-Mo:C & -10.6 & -81.222 & 60.022 & 0.999 \tabularnewline
SM:C-Mo:C & 5.35 & -65.272 & 75.972 & 1 \tabularnewline
Mo:M-Mo:C & 33.6 & -37.022 & 104.222 & 0.639 \tabularnewline
Rq:M-Mo:C & -1 & -71.622 & 69.622 & 1 \tabularnewline
SM:M-Mo:C & 27.9 & -42.722 & 98.522 & 0.803 \tabularnewline
SM:C-Rq:C & 15.95 & -54.672 & 86.572 & 0.988 \tabularnewline
Mo:M-Rq:C & 44.2 & -26.422 & 114.822 & 0.349 \tabularnewline
Rq:M-Rq:C & 9.6 & -61.022 & 80.222 & 1 \tabularnewline
SM:M-Rq:C & 38.5 & -32.122 & 109.122 & 0.495 \tabularnewline
Mo:M-SM:C & 28.25 & -42.372 & 98.872 & 0.794 \tabularnewline
Rq:M-SM:C & -6.35 & -76.972 & 64.272 & 1 \tabularnewline
SM:M-SM:C & 22.55 & -48.072 & 93.172 & 0.92 \tabularnewline
Rq:M-Mo:M & -34.6 & -105.222 & 36.022 & 0.609 \tabularnewline
SM:M-Mo:M & -5.7 & -76.322 & 64.922 & 1 \tabularnewline
SM:M-Rq:M & 28.9 & -41.722 & 99.522 & 0.776 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168762&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]Rq-Mo[/C][C]-27.1[/C][C]-55.876[/C][C]1.676[/C][C]0.064[/C][/ROW]
[ROW][C]SM-Mo[/C][C]-3.983[/C][C]-32.759[/C][C]24.793[/C][C]0.922[/C][/ROW]
[ROW][C]SM-Rq[/C][C]23.117[/C][C]-5.659[/C][C]51.893[/C][C]0.117[/C][/ROW]
[ROW][C]C-0[/C][C]-7.75[/C][C]-36.526[/C][C]21.026[/C][C]0.74[/C][/ROW]
[ROW][C]M-0[/C][C]14.167[/C][C]-14.609[/C][C]42.943[/C][C]0.393[/C][/ROW]
[ROW][C]M-C[/C][C]21.917[/C][C]-6.859[/C][C]50.693[/C][C]0.139[/C][/ROW]
[ROW][C]Rq:0-Mo:0[/C][C]-36.1[/C][C]-106.722[/C][C]34.522[/C][C]0.564[/C][/ROW]
[ROW][C]SM:0-Mo:0[/C][C]-11.6[/C][C]-82.222[/C][C]59.022[/C][C]0.998[/C][/ROW]
[ROW][C]Mo:C-Mo:0[/C][C]-21.9[/C][C]-92.522[/C][C]48.722[/C][C]0.93[/C][/ROW]
[ROW][C]Rq:C-Mo:0[/C][C]-32.5[/C][C]-103.122[/C][C]38.122[/C][C]0.672[/C][/ROW]
[ROW][C]SM:C-Mo:0[/C][C]-16.55[/C][C]-87.172[/C][C]54.072[/C][C]0.985[/C][/ROW]
[ROW][C]Mo:M-Mo:0[/C][C]11.7[/C][C]-58.922[/C][C]82.322[/C][C]0.998[/C][/ROW]
[ROW][C]Rq:M-Mo:0[/C][C]-22.9[/C][C]-93.522[/C][C]47.722[/C][C]0.914[/C][/ROW]
[ROW][C]SM:M-Mo:0[/C][C]6[/C][C]-64.622[/C][C]76.622[/C][C]1[/C][/ROW]
[ROW][C]SM:0-Rq:0[/C][C]24.5[/C][C]-46.122[/C][C]95.122[/C][C]0.883[/C][/ROW]
[ROW][C]Mo:C-Rq:0[/C][C]14.2[/C][C]-56.422[/C][C]84.822[/C][C]0.994[/C][/ROW]
[ROW][C]Rq:C-Rq:0[/C][C]3.6[/C][C]-67.022[/C][C]74.222[/C][C]1[/C][/ROW]
[ROW][C]SM:C-Rq:0[/C][C]19.55[/C][C]-51.072[/C][C]90.172[/C][C]0.961[/C][/ROW]
[ROW][C]Mo:M-Rq:0[/C][C]47.8[/C][C]-22.822[/C][C]118.422[/C][C]0.273[/C][/ROW]
[ROW][C]Rq:M-Rq:0[/C][C]13.2[/C][C]-57.422[/C][C]83.822[/C][C]0.996[/C][/ROW]
[ROW][C]SM:M-Rq:0[/C][C]42.1[/C][C]-28.522[/C][C]112.722[/C][C]0.399[/C][/ROW]
[ROW][C]Mo:C-SM:0[/C][C]-10.3[/C][C]-80.922[/C][C]60.322[/C][C]0.999[/C][/ROW]
[ROW][C]Rq:C-SM:0[/C][C]-20.9[/C][C]-91.522[/C][C]49.722[/C][C]0.945[/C][/ROW]
[ROW][C]SM:C-SM:0[/C][C]-4.95[/C][C]-75.572[/C][C]65.672[/C][C]1[/C][/ROW]
[ROW][C]Mo:M-SM:0[/C][C]23.3[/C][C]-47.322[/C][C]93.922[/C][C]0.907[/C][/ROW]
[ROW][C]Rq:M-SM:0[/C][C]-11.3[/C][C]-81.922[/C][C]59.322[/C][C]0.999[/C][/ROW]
[ROW][C]SM:M-SM:0[/C][C]17.6[/C][C]-53.022[/C][C]88.222[/C][C]0.978[/C][/ROW]
[ROW][C]Rq:C-Mo:C[/C][C]-10.6[/C][C]-81.222[/C][C]60.022[/C][C]0.999[/C][/ROW]
[ROW][C]SM:C-Mo:C[/C][C]5.35[/C][C]-65.272[/C][C]75.972[/C][C]1[/C][/ROW]
[ROW][C]Mo:M-Mo:C[/C][C]33.6[/C][C]-37.022[/C][C]104.222[/C][C]0.639[/C][/ROW]
[ROW][C]Rq:M-Mo:C[/C][C]-1[/C][C]-71.622[/C][C]69.622[/C][C]1[/C][/ROW]
[ROW][C]SM:M-Mo:C[/C][C]27.9[/C][C]-42.722[/C][C]98.522[/C][C]0.803[/C][/ROW]
[ROW][C]SM:C-Rq:C[/C][C]15.95[/C][C]-54.672[/C][C]86.572[/C][C]0.988[/C][/ROW]
[ROW][C]Mo:M-Rq:C[/C][C]44.2[/C][C]-26.422[/C][C]114.822[/C][C]0.349[/C][/ROW]
[ROW][C]Rq:M-Rq:C[/C][C]9.6[/C][C]-61.022[/C][C]80.222[/C][C]1[/C][/ROW]
[ROW][C]SM:M-Rq:C[/C][C]38.5[/C][C]-32.122[/C][C]109.122[/C][C]0.495[/C][/ROW]
[ROW][C]Mo:M-SM:C[/C][C]28.25[/C][C]-42.372[/C][C]98.872[/C][C]0.794[/C][/ROW]
[ROW][C]Rq:M-SM:C[/C][C]-6.35[/C][C]-76.972[/C][C]64.272[/C][C]1[/C][/ROW]
[ROW][C]SM:M-SM:C[/C][C]22.55[/C][C]-48.072[/C][C]93.172[/C][C]0.92[/C][/ROW]
[ROW][C]Rq:M-Mo:M[/C][C]-34.6[/C][C]-105.222[/C][C]36.022[/C][C]0.609[/C][/ROW]
[ROW][C]SM:M-Mo:M[/C][C]-5.7[/C][C]-76.322[/C][C]64.922[/C][C]1[/C][/ROW]
[ROW][C]SM:M-Rq:M[/C][C]28.9[/C][C]-41.722[/C][C]99.522[/C][C]0.776[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168762&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168762&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
Rq-Mo-27.1-55.8761.6760.064
SM-Mo-3.983-32.75924.7930.922
SM-Rq23.117-5.65951.8930.117
C-0-7.75-36.52621.0260.74
M-014.167-14.60942.9430.393
M-C21.917-6.85950.6930.139
Rq:0-Mo:0-36.1-106.72234.5220.564
SM:0-Mo:0-11.6-82.22259.0220.998
Mo:C-Mo:0-21.9-92.52248.7220.93
Rq:C-Mo:0-32.5-103.12238.1220.672
SM:C-Mo:0-16.55-87.17254.0720.985
Mo:M-Mo:011.7-58.92282.3220.998
Rq:M-Mo:0-22.9-93.52247.7220.914
SM:M-Mo:06-64.62276.6221
SM:0-Rq:024.5-46.12295.1220.883
Mo:C-Rq:014.2-56.42284.8220.994
Rq:C-Rq:03.6-67.02274.2221
SM:C-Rq:019.55-51.07290.1720.961
Mo:M-Rq:047.8-22.822118.4220.273
Rq:M-Rq:013.2-57.42283.8220.996
SM:M-Rq:042.1-28.522112.7220.399
Mo:C-SM:0-10.3-80.92260.3220.999
Rq:C-SM:0-20.9-91.52249.7220.945
SM:C-SM:0-4.95-75.57265.6721
Mo:M-SM:023.3-47.32293.9220.907
Rq:M-SM:0-11.3-81.92259.3220.999
SM:M-SM:017.6-53.02288.2220.978
Rq:C-Mo:C-10.6-81.22260.0220.999
SM:C-Mo:C5.35-65.27275.9721
Mo:M-Mo:C33.6-37.022104.2220.639
Rq:M-Mo:C-1-71.62269.6221
SM:M-Mo:C27.9-42.72298.5220.803
SM:C-Rq:C15.95-54.67286.5720.988
Mo:M-Rq:C44.2-26.422114.8220.349
Rq:M-Rq:C9.6-61.02280.2221
SM:M-Rq:C38.5-32.122109.1220.495
Mo:M-SM:C28.25-42.37298.8720.794
Rq:M-SM:C-6.35-76.97264.2721
SM:M-SM:C22.55-48.07293.1720.92
Rq:M-Mo:M-34.6-105.22236.0220.609
SM:M-Mo:M-5.7-76.32264.9221
SM:M-Rq:M28.9-41.72299.5220.776







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group83.80054648365029e+310
9

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 3.80054648365029e+31 & 0 \tabularnewline
  & 9 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168762&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]3.80054648365029e+31[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]9[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168762&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168762&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)
Group83.80054648365029e+310
9



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):
par4 <- 'FALSE'
par3 <- '3'
par2 <- '2'
par1 <- '1'
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')