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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, 28 Nov 2017 21:00:04 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Nov/28/t1511899368sbnw24im1eszukv.htm/, Retrieved Sat, 18 May 2024 17:57:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308272, Retrieved Sat, 18 May 2024 17:57:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsITU - SQ1 - Gender
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [2WayANOVA] [2017-11-28 20:00:04] [e32c8f3a6c40fa6b5d041988204898ea] [Current]
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Dataseries X:
10 3 0
8 2 1
8 4 1
9 4 1
5 3 0
10 4 1
8 2 1
9 3 1
8 3 0
7 5 0
10 4 0
10 3 0
9 4 1
4 3 0
4 4 1
8 5 1
9 3 1
10 3 1
8 4 0
5 4 0
10 4 1
8 2 0
7 3 1
8 4 1
8 4 1
9 3 0
8 3 0
6 3 1
8 4 1
8 2 0
5 5 1
9 2 1
8 3 0
8 3 0
8 3 0
6 4 0
6 3 0
9 3 1
8 4 1
9 5 1
10 3 1
8 3 0
8 2 0
7 4 0
7 4 1
10 4 1
8 3 1
7 4 1
10 4 1
7 3 1
7 3 0
9 5 0
9 5 0
8 4 0
6 3 0
8 4 0
9 3 1
2 4 0
6 5 0
8 3 1
8 4 1
7 3 0
8 2 0
6 2 0
10 2 0
10 3 0
10 3 0
8 3 0
8 3 1
7 3 1
10 5 1
5 3 0
3 1 1
2 1 1
3 3 1
4 1 1
2 3 0
6 2 0
8 4 0
8 4 0
5 1 0
10 4 1
9 3 1
8 3 1
9 4 1
8 4 1
5 3 0
7 4 1
9 4 1
8 2 0
4 4 1
7 2 1
8 4 1
7 4 0
7 4 1
9 4 0
6 4 1
7 4 0
4 2 0
6 4 1
10 5 0
9 4 1
10 5 1
8 4 0
4 4 0
8 5 1
5 4 0
8 4 1
9 4 1
8 3 0
4 5 1
8 3 0
10 4 1
6 2 0
7 4 0
10 3 1
9 4 1
8 5 1
3 2 0
8 3 0
7 2 0
7 3 0
8 3 0
8 4 1
7 5 0
7 4 1
9 5 0
9 4 1
9 4 0
4 3 1
6 3 0
6 3 1
6 3 0
8 4 0
3 2 0
8 5 0
8 4 1
6 2 1
10 4 0
2 3 0
9 4 1
6 4 1
6 3 0
5 2 0
4 2 0
7 4 0
5 1 1
8 4 1
6 4 0
9 5 1
6 3 0
4 1 1
7 3 0
2 1 1
8 5 1
9 3 1
6 4 0
5 2 1
7 4 1
8 4 1
4 4 0
9 4 1
9 4 0
9 4 1
7 3 0
5 4 1
7 3 0
9 5 1
8 4 1
6 3 1
9 5 1
8 3 1
7 5 1
7 2 0
7 5 0
8 3 0
10 4 1
6 4 0




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time5 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308272&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]5 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308272&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308272&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center







ANOVA Model
Response ~ Treatment_A * Treatment_B
means51.3132.02923-1.6672.5212.3652.7121.667

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 5 & 1.313 & 2.029 & 2 & 3 & -1.667 & 2.521 & 2.365 & 2.712 & 1.667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308272&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]5[/C][C]1.313[/C][C]2.029[/C][C]2[/C][C]3[/C][C]-1.667[/C][C]2.521[/C][C]2.365[/C][C]2.712[/C][C]1.667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308272&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308272&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
means51.3132.02923-1.6672.5212.3652.7121.667







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
4
Treatment_A4129.51832.37910.3640
Treatment_B420.56820.5686.5840.011
Treatment_A:Treatment_B49.4532.3630.7560.555
Residuals168524.8483.124

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 4 &  &  &  &  \tabularnewline
Treatment_A & 4 & 129.518 & 32.379 & 10.364 & 0 \tabularnewline
Treatment_B & 4 & 20.568 & 20.568 & 6.584 & 0.011 \tabularnewline
Treatment_A:Treatment_B & 4 & 9.453 & 2.363 & 0.756 & 0.555 \tabularnewline
Residuals & 168 & 524.848 & 3.124 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308272&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]4[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]4[/C][C]129.518[/C][C]32.379[/C][C]10.364[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]4[/C][C]20.568[/C][C]20.568[/C][C]6.584[/C][C]0.011[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]4[/C][C]9.453[/C][C]2.363[/C][C]0.756[/C][C]0.555[/C][/ROW]
[ROW][C]Residuals[/C][C]168[/C][C]524.848[/C][C]3.124[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308272&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308272&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)
4
Treatment_A4129.51832.37910.3640
Treatment_B420.56820.5686.5840.011
Treatment_A:Treatment_B49.4532.3630.7560.555
Residuals168524.8483.124







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-12.9740.8595.0890.001
3-13.7271.7755.6790
4-14.0862.1546.0180
5-14.4292.3136.5440
3-20.753-0.4711.9760.439
4-21.112-0.082.3030.08
5-21.455-0.0152.9240.054
4-30.359-0.5111.2280.786
5-30.702-0.5221.9250.511
5-40.343-0.8481.5340.932
1-00.6480.1251.1710.016
2:0-1:01.313-4.537.1550.999
3:0-1:02.029-3.727.7770.981
4:0-1:02-3.7767.7760.983
5:0-1:03-2.9758.9750.842
1:1-1:0-1.667-7.7894.4550.997
2:1-1:02.167-3.9558.2890.98
3:1-1:02.727-3.0688.5230.887
4:1-1:03.045-2.6878.7770.792
5:1-1:03-2.8828.8820.829
3:0-2:00.716-0.9942.4270.942
4:0-2:00.687-1.1132.4880.968
5:0-2:01.687-0.6744.0490.4
1:1-2:0-2.979-5.692-0.2660.019
2:1-2:00.854-1.8593.5670.991
3:1-2:01.415-0.4483.2770.312
4:1-2:01.7330.0783.3880.032
5:1-2:01.687-0.4293.8040.247
4:0-3:0-0.029-1.4961.4391
5:0-3:00.971-1.1473.090.902
1:1-3:0-3.695-6.2-1.1910
2:1-3:00.138-2.3662.6431
3:1-3:00.699-0.8432.2410.908
4:1-3:01.017-0.2672.3010.255
5:1-3:00.971-0.872.8120.798
5:0-4:01-1.1923.1920.905
1:1-4:0-3.667-6.234-1.10
2:1-4:00.167-2.42.7341
3:1-4:00.727-0.9152.3690.919
4:1-4:01.045-0.3572.4470.338
5:1-4:01-0.9252.9250.813
1:1-5:0-4.667-7.654-1.6790
2:1-5:0-0.833-3.8212.1540.996
3:1-5:0-0.273-2.5151.971
4:1-5:00.045-2.0282.1191
5:1-5:00-2.4582.4581
2:1-1:13.8330.5617.1060.009
3:1-1:14.3941.7837.0040
4:1-1:14.7122.2457.1790
5:1-1:14.6671.8697.4640
3:1-2:10.561-2.053.1711
4:1-2:10.879-1.5883.3450.979
5:1-2:10.833-1.9643.6310.994
4:1-3:10.318-1.1621.7981
5:1-3:10.273-1.712.2561
5:1-4:1-0.045-1.8351.7441

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 2.974 & 0.859 & 5.089 & 0.001 \tabularnewline
3-1 & 3.727 & 1.775 & 5.679 & 0 \tabularnewline
4-1 & 4.086 & 2.154 & 6.018 & 0 \tabularnewline
5-1 & 4.429 & 2.313 & 6.544 & 0 \tabularnewline
3-2 & 0.753 & -0.471 & 1.976 & 0.439 \tabularnewline
4-2 & 1.112 & -0.08 & 2.303 & 0.08 \tabularnewline
5-2 & 1.455 & -0.015 & 2.924 & 0.054 \tabularnewline
4-3 & 0.359 & -0.511 & 1.228 & 0.786 \tabularnewline
5-3 & 0.702 & -0.522 & 1.925 & 0.511 \tabularnewline
5-4 & 0.343 & -0.848 & 1.534 & 0.932 \tabularnewline
1-0 & 0.648 & 0.125 & 1.171 & 0.016 \tabularnewline
2:0-1:0 & 1.313 & -4.53 & 7.155 & 0.999 \tabularnewline
3:0-1:0 & 2.029 & -3.72 & 7.777 & 0.981 \tabularnewline
4:0-1:0 & 2 & -3.776 & 7.776 & 0.983 \tabularnewline
5:0-1:0 & 3 & -2.975 & 8.975 & 0.842 \tabularnewline
1:1-1:0 & -1.667 & -7.789 & 4.455 & 0.997 \tabularnewline
2:1-1:0 & 2.167 & -3.955 & 8.289 & 0.98 \tabularnewline
3:1-1:0 & 2.727 & -3.068 & 8.523 & 0.887 \tabularnewline
4:1-1:0 & 3.045 & -2.687 & 8.777 & 0.792 \tabularnewline
5:1-1:0 & 3 & -2.882 & 8.882 & 0.829 \tabularnewline
3:0-2:0 & 0.716 & -0.994 & 2.427 & 0.942 \tabularnewline
4:0-2:0 & 0.687 & -1.113 & 2.488 & 0.968 \tabularnewline
5:0-2:0 & 1.687 & -0.674 & 4.049 & 0.4 \tabularnewline
1:1-2:0 & -2.979 & -5.692 & -0.266 & 0.019 \tabularnewline
2:1-2:0 & 0.854 & -1.859 & 3.567 & 0.991 \tabularnewline
3:1-2:0 & 1.415 & -0.448 & 3.277 & 0.312 \tabularnewline
4:1-2:0 & 1.733 & 0.078 & 3.388 & 0.032 \tabularnewline
5:1-2:0 & 1.687 & -0.429 & 3.804 & 0.247 \tabularnewline
4:0-3:0 & -0.029 & -1.496 & 1.439 & 1 \tabularnewline
5:0-3:0 & 0.971 & -1.147 & 3.09 & 0.902 \tabularnewline
1:1-3:0 & -3.695 & -6.2 & -1.191 & 0 \tabularnewline
2:1-3:0 & 0.138 & -2.366 & 2.643 & 1 \tabularnewline
3:1-3:0 & 0.699 & -0.843 & 2.241 & 0.908 \tabularnewline
4:1-3:0 & 1.017 & -0.267 & 2.301 & 0.255 \tabularnewline
5:1-3:0 & 0.971 & -0.87 & 2.812 & 0.798 \tabularnewline
5:0-4:0 & 1 & -1.192 & 3.192 & 0.905 \tabularnewline
1:1-4:0 & -3.667 & -6.234 & -1.1 & 0 \tabularnewline
2:1-4:0 & 0.167 & -2.4 & 2.734 & 1 \tabularnewline
3:1-4:0 & 0.727 & -0.915 & 2.369 & 0.919 \tabularnewline
4:1-4:0 & 1.045 & -0.357 & 2.447 & 0.338 \tabularnewline
5:1-4:0 & 1 & -0.925 & 2.925 & 0.813 \tabularnewline
1:1-5:0 & -4.667 & -7.654 & -1.679 & 0 \tabularnewline
2:1-5:0 & -0.833 & -3.821 & 2.154 & 0.996 \tabularnewline
3:1-5:0 & -0.273 & -2.515 & 1.97 & 1 \tabularnewline
4:1-5:0 & 0.045 & -2.028 & 2.119 & 1 \tabularnewline
5:1-5:0 & 0 & -2.458 & 2.458 & 1 \tabularnewline
2:1-1:1 & 3.833 & 0.561 & 7.106 & 0.009 \tabularnewline
3:1-1:1 & 4.394 & 1.783 & 7.004 & 0 \tabularnewline
4:1-1:1 & 4.712 & 2.245 & 7.179 & 0 \tabularnewline
5:1-1:1 & 4.667 & 1.869 & 7.464 & 0 \tabularnewline
3:1-2:1 & 0.561 & -2.05 & 3.171 & 1 \tabularnewline
4:1-2:1 & 0.879 & -1.588 & 3.345 & 0.979 \tabularnewline
5:1-2:1 & 0.833 & -1.964 & 3.631 & 0.994 \tabularnewline
4:1-3:1 & 0.318 & -1.162 & 1.798 & 1 \tabularnewline
5:1-3:1 & 0.273 & -1.71 & 2.256 & 1 \tabularnewline
5:1-4:1 & -0.045 & -1.835 & 1.744 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308272&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]2-1[/C][C]2.974[/C][C]0.859[/C][C]5.089[/C][C]0.001[/C][/ROW]
[ROW][C]3-1[/C][C]3.727[/C][C]1.775[/C][C]5.679[/C][C]0[/C][/ROW]
[ROW][C]4-1[/C][C]4.086[/C][C]2.154[/C][C]6.018[/C][C]0[/C][/ROW]
[ROW][C]5-1[/C][C]4.429[/C][C]2.313[/C][C]6.544[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]0.753[/C][C]-0.471[/C][C]1.976[/C][C]0.439[/C][/ROW]
[ROW][C]4-2[/C][C]1.112[/C][C]-0.08[/C][C]2.303[/C][C]0.08[/C][/ROW]
[ROW][C]5-2[/C][C]1.455[/C][C]-0.015[/C][C]2.924[/C][C]0.054[/C][/ROW]
[ROW][C]4-3[/C][C]0.359[/C][C]-0.511[/C][C]1.228[/C][C]0.786[/C][/ROW]
[ROW][C]5-3[/C][C]0.702[/C][C]-0.522[/C][C]1.925[/C][C]0.511[/C][/ROW]
[ROW][C]5-4[/C][C]0.343[/C][C]-0.848[/C][C]1.534[/C][C]0.932[/C][/ROW]
[ROW][C]1-0[/C][C]0.648[/C][C]0.125[/C][C]1.171[/C][C]0.016[/C][/ROW]
[ROW][C]2:0-1:0[/C][C]1.313[/C][C]-4.53[/C][C]7.155[/C][C]0.999[/C][/ROW]
[ROW][C]3:0-1:0[/C][C]2.029[/C][C]-3.72[/C][C]7.777[/C][C]0.981[/C][/ROW]
[ROW][C]4:0-1:0[/C][C]2[/C][C]-3.776[/C][C]7.776[/C][C]0.983[/C][/ROW]
[ROW][C]5:0-1:0[/C][C]3[/C][C]-2.975[/C][C]8.975[/C][C]0.842[/C][/ROW]
[ROW][C]1:1-1:0[/C][C]-1.667[/C][C]-7.789[/C][C]4.455[/C][C]0.997[/C][/ROW]
[ROW][C]2:1-1:0[/C][C]2.167[/C][C]-3.955[/C][C]8.289[/C][C]0.98[/C][/ROW]
[ROW][C]3:1-1:0[/C][C]2.727[/C][C]-3.068[/C][C]8.523[/C][C]0.887[/C][/ROW]
[ROW][C]4:1-1:0[/C][C]3.045[/C][C]-2.687[/C][C]8.777[/C][C]0.792[/C][/ROW]
[ROW][C]5:1-1:0[/C][C]3[/C][C]-2.882[/C][C]8.882[/C][C]0.829[/C][/ROW]
[ROW][C]3:0-2:0[/C][C]0.716[/C][C]-0.994[/C][C]2.427[/C][C]0.942[/C][/ROW]
[ROW][C]4:0-2:0[/C][C]0.687[/C][C]-1.113[/C][C]2.488[/C][C]0.968[/C][/ROW]
[ROW][C]5:0-2:0[/C][C]1.687[/C][C]-0.674[/C][C]4.049[/C][C]0.4[/C][/ROW]
[ROW][C]1:1-2:0[/C][C]-2.979[/C][C]-5.692[/C][C]-0.266[/C][C]0.019[/C][/ROW]
[ROW][C]2:1-2:0[/C][C]0.854[/C][C]-1.859[/C][C]3.567[/C][C]0.991[/C][/ROW]
[ROW][C]3:1-2:0[/C][C]1.415[/C][C]-0.448[/C][C]3.277[/C][C]0.312[/C][/ROW]
[ROW][C]4:1-2:0[/C][C]1.733[/C][C]0.078[/C][C]3.388[/C][C]0.032[/C][/ROW]
[ROW][C]5:1-2:0[/C][C]1.687[/C][C]-0.429[/C][C]3.804[/C][C]0.247[/C][/ROW]
[ROW][C]4:0-3:0[/C][C]-0.029[/C][C]-1.496[/C][C]1.439[/C][C]1[/C][/ROW]
[ROW][C]5:0-3:0[/C][C]0.971[/C][C]-1.147[/C][C]3.09[/C][C]0.902[/C][/ROW]
[ROW][C]1:1-3:0[/C][C]-3.695[/C][C]-6.2[/C][C]-1.191[/C][C]0[/C][/ROW]
[ROW][C]2:1-3:0[/C][C]0.138[/C][C]-2.366[/C][C]2.643[/C][C]1[/C][/ROW]
[ROW][C]3:1-3:0[/C][C]0.699[/C][C]-0.843[/C][C]2.241[/C][C]0.908[/C][/ROW]
[ROW][C]4:1-3:0[/C][C]1.017[/C][C]-0.267[/C][C]2.301[/C][C]0.255[/C][/ROW]
[ROW][C]5:1-3:0[/C][C]0.971[/C][C]-0.87[/C][C]2.812[/C][C]0.798[/C][/ROW]
[ROW][C]5:0-4:0[/C][C]1[/C][C]-1.192[/C][C]3.192[/C][C]0.905[/C][/ROW]
[ROW][C]1:1-4:0[/C][C]-3.667[/C][C]-6.234[/C][C]-1.1[/C][C]0[/C][/ROW]
[ROW][C]2:1-4:0[/C][C]0.167[/C][C]-2.4[/C][C]2.734[/C][C]1[/C][/ROW]
[ROW][C]3:1-4:0[/C][C]0.727[/C][C]-0.915[/C][C]2.369[/C][C]0.919[/C][/ROW]
[ROW][C]4:1-4:0[/C][C]1.045[/C][C]-0.357[/C][C]2.447[/C][C]0.338[/C][/ROW]
[ROW][C]5:1-4:0[/C][C]1[/C][C]-0.925[/C][C]2.925[/C][C]0.813[/C][/ROW]
[ROW][C]1:1-5:0[/C][C]-4.667[/C][C]-7.654[/C][C]-1.679[/C][C]0[/C][/ROW]
[ROW][C]2:1-5:0[/C][C]-0.833[/C][C]-3.821[/C][C]2.154[/C][C]0.996[/C][/ROW]
[ROW][C]3:1-5:0[/C][C]-0.273[/C][C]-2.515[/C][C]1.97[/C][C]1[/C][/ROW]
[ROW][C]4:1-5:0[/C][C]0.045[/C][C]-2.028[/C][C]2.119[/C][C]1[/C][/ROW]
[ROW][C]5:1-5:0[/C][C]0[/C][C]-2.458[/C][C]2.458[/C][C]1[/C][/ROW]
[ROW][C]2:1-1:1[/C][C]3.833[/C][C]0.561[/C][C]7.106[/C][C]0.009[/C][/ROW]
[ROW][C]3:1-1:1[/C][C]4.394[/C][C]1.783[/C][C]7.004[/C][C]0[/C][/ROW]
[ROW][C]4:1-1:1[/C][C]4.712[/C][C]2.245[/C][C]7.179[/C][C]0[/C][/ROW]
[ROW][C]5:1-1:1[/C][C]4.667[/C][C]1.869[/C][C]7.464[/C][C]0[/C][/ROW]
[ROW][C]3:1-2:1[/C][C]0.561[/C][C]-2.05[/C][C]3.171[/C][C]1[/C][/ROW]
[ROW][C]4:1-2:1[/C][C]0.879[/C][C]-1.588[/C][C]3.345[/C][C]0.979[/C][/ROW]
[ROW][C]5:1-2:1[/C][C]0.833[/C][C]-1.964[/C][C]3.631[/C][C]0.994[/C][/ROW]
[ROW][C]4:1-3:1[/C][C]0.318[/C][C]-1.162[/C][C]1.798[/C][C]1[/C][/ROW]
[ROW][C]5:1-3:1[/C][C]0.273[/C][C]-1.71[/C][C]2.256[/C][C]1[/C][/ROW]
[ROW][C]5:1-4:1[/C][C]-0.045[/C][C]-1.835[/C][C]1.744[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308272&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308272&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
2-12.9740.8595.0890.001
3-13.7271.7755.6790
4-14.0862.1546.0180
5-14.4292.3136.5440
3-20.753-0.4711.9760.439
4-21.112-0.082.3030.08
5-21.455-0.0152.9240.054
4-30.359-0.5111.2280.786
5-30.702-0.5221.9250.511
5-40.343-0.8481.5340.932
1-00.6480.1251.1710.016
2:0-1:01.313-4.537.1550.999
3:0-1:02.029-3.727.7770.981
4:0-1:02-3.7767.7760.983
5:0-1:03-2.9758.9750.842
1:1-1:0-1.667-7.7894.4550.997
2:1-1:02.167-3.9558.2890.98
3:1-1:02.727-3.0688.5230.887
4:1-1:03.045-2.6878.7770.792
5:1-1:03-2.8828.8820.829
3:0-2:00.716-0.9942.4270.942
4:0-2:00.687-1.1132.4880.968
5:0-2:01.687-0.6744.0490.4
1:1-2:0-2.979-5.692-0.2660.019
2:1-2:00.854-1.8593.5670.991
3:1-2:01.415-0.4483.2770.312
4:1-2:01.7330.0783.3880.032
5:1-2:01.687-0.4293.8040.247
4:0-3:0-0.029-1.4961.4391
5:0-3:00.971-1.1473.090.902
1:1-3:0-3.695-6.2-1.1910
2:1-3:00.138-2.3662.6431
3:1-3:00.699-0.8432.2410.908
4:1-3:01.017-0.2672.3010.255
5:1-3:00.971-0.872.8120.798
5:0-4:01-1.1923.1920.905
1:1-4:0-3.667-6.234-1.10
2:1-4:00.167-2.42.7341
3:1-4:00.727-0.9152.3690.919
4:1-4:01.045-0.3572.4470.338
5:1-4:01-0.9252.9250.813
1:1-5:0-4.667-7.654-1.6790
2:1-5:0-0.833-3.8212.1540.996
3:1-5:0-0.273-2.5151.971
4:1-5:00.045-2.0282.1191
5:1-5:00-2.4582.4581
2:1-1:13.8330.5617.1060.009
3:1-1:14.3941.7837.0040
4:1-1:14.7122.2457.1790
5:1-1:14.6671.8697.4640
3:1-2:10.561-2.053.1711
4:1-2:10.879-1.5883.3450.979
5:1-2:10.833-1.9643.6310.994
4:1-3:10.318-1.1621.7981
5:1-3:10.273-1.712.2561
5:1-4:1-0.045-1.8351.7441







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group90.7550.659
168

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 9 & 0.755 & 0.659 \tabularnewline
  & 168 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308272&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]9[/C][C]0.755[/C][C]0.659[/C][/ROW]
[ROW][C] [/C][C]168[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308272&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308272&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)
Group90.7550.659
168



Parameters (Session):
par1 = grey ; par2 = no ;
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')