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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationMon, 01 Dec 2014 11:21:17 +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/2014/Dec/01/t1417432899s31thrno7jcmm5m.htm/, Retrieved Thu, 16 May 2024 15:17:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261730, Retrieved Thu, 16 May 2024 15:17:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101

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)] [] [2014-10-18 18:42:11] [8f0f7d8870e334acea674e48ede2c797]
-    D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-Way Anova ] [2014-12-01 11:21:17] [310e7528d8f6aa5642dc98f4186768d1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9 5 4
9 6 6
8 5 5
8 4 6
8 5 5
8 7 4
7 3 0
8 4 5
9 4 3
8 7 5
7 6 2
9 6 3
7 2 4
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8 4 3
8 5 4
8 3 1
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6 7 4
9 5 4
7 2 4
7 3 3
8 6 6
7 6 5
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3 2 4
9 10 6
8 4 5
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6 2 5
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3 3 3
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8 4 6
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9 4 6
6 3 5
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7 2 4
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3 2 2
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6 2 0
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6 3 1
2 4 1
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6 4 6
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9 4 5
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6 4 5
8 2 6
3 0 0
8 4 6
7 3 4
7 6 6
9 4 4
4 4 6
7 2 4
6 4 5
3 2 1
8 4 5
8 3 5
9 6 5
8 6 5
8 4 5
9 5 6
8 4 5
9 6 6
7 6 5
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6 4 5
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6 5 5
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7 4 6
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6 5 6
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9 4 5
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8 5 6
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9 4 4
6 5 6
9 5 4
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8 7 6
8 5 3
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8 7 4
8 7 6
3 1 4
6 2 4
5 3 2
4 6 5
9 8 6
8 8 6
3 0 1
6 3 4
6 6 5
9 5 5
7 7 6
6 3 5
9 3 6
7 4 6
8 4 5
8 1 5
8 5 6
7 3 4
0 0 0
6 4 6
9 6 5
9 4 6
6 1 2
8 3 5
8 7 5
5 3 1
6 5 5
6 3 4
9 3 5
9 6 4
9 9 6
6 4 5
4 3 6
8 9 6
4 5 6
5 3 6
8 6 5
6 2 6
8 4 5
9 5 5
7 4 5
4 0 0
8 2 6
8 5 6
8 3 6
4 0 0
9 5 5
8 6 5
6 3 5
3 0 0
7 3 4
8 5 6
7 4 4
7 5 5
8 7 6
8 4 5
7 8 6
7 6 6
6 4 5
8 5 5
8 5 6
7 3 6
9 6 6
9 3 4
7 6 5
7 3 2
8 7 6
8 7 6
6 6 4
9 5 6
6 5 5
5 4 4
7 4 6
9 7 6
6 2 1
7 5 5
5 4 5
9 2 6
8 5 4
4 4 3
9 7 4
8 6 5
7 4 5
8 5 6
1 0 1
8 7 6
8 4 4
9 5 4
8 6 5
9 8 3
6 5 6
7 5 2
8 5 6
8 5 6
9 8 5
9 7 6
7 3 6
8 4 6
2 5 6
4 1 2
5 6 5
8 7 6
6 5 4
9 7 5
8 5 5
4 5 4
7 3 6
NA NA NA
7 5 6
8 5 5
5 3 6
5 5 5
7 7 6
7 4 6
8 5 2
6 3 5
7 5 5
NA NA NA
8 7 6
8 1 4
7 5 6
9 5 6
8 9 6
6 4 5
8 5 3
5 5 6
3 5 4
6 2 6
4 4 4
5 4 6
9 4 5
5 3 4
6 6 6
7 5 0
6 6 4
9 7 5
6 4 4
7 4 5
8 4 5
5 5 4
4 2 5
4 2 2
4 3 6
5 6 2
4 8 4
6 4 5
5 5 3
5 6 2
6 3 6
5 4 3
7 5 6
6 4 5
6 3 5
8 5 6
7 5 5
9 3 5
4 4 5
7 5 5
7 7 5
8 9 6
8 8 5
7 6 6
7 4 4
9 7 5
6 3 5
7 5 6
8 6 6
5 6 3
5 7 6
5 3 4
8 6 5
5 6 6
7 4 6
6 4 5
5 5 5
7 4 5
6 5 4
8 9 1
9 6 5
7 4 5
7 4 4
9 4 5
7 5 6
7 6 4
6 3 5
8 8 6
8 4 4
7 4 6
5 4 4
6 6 4
8 8 6
7 6 4
6 3 5
4 4 4
6 4 6
7 6 6
8 9 5
7 6 6
8 4 6
9 4 4
8 5 5
7 4 6
4 3 6
6 5 6
7 4 6
8 6 6
6 5 6
7 4 6
8 6 6
7 8 6
8 4 4
9 4 0
7 7 6
8 8 5
8 7 5
9 6 6
6 3 5
8 2 2
8 5 6
9 6 6
7 4 4
6 5 4
5 5 6
8 4 5
8 3 6
6 5 6
4 2 5
9 7 3
6 5 4
5 4 5
8 8 6
9 3 6
4 2 5
7 4 6
5 3 6
8 5 5
7 5 5
8 3 6
6 7 4
9 6 4
5 4 1
6 4 5
7 6 5
9 7 6
6 4 3
6 9 4
9 7 5
9 7 2
6 5 6
6 5 1
9 5 6
8 6 6
6 4 6
6 4 5
7 6 2
7 4 1
2 3 4
NA NA NA
6 3 6
9 2 5
6 6 3
5 3 4
6 4 5
8 3 4
3 4 4
6 8 5
8 5 5
9 5 6
9 5 6
8 5 3
9 7 4
7 3 5
5 5 3
7 5 5
9 5 5
9 5 6
8 5 6
8 4 2
6 9 6
9 5 5
8 4 4
9 8 6
8 5 3
7 2 5
8 5 6
7 7 5
5 3 6
7 5 4
7 5 6
6 4 6
7 1 4
6 6 6
9 5 4
6 5 5
7 4 5
4 4 4
8 5 4
6 5 5
5 4 2
7 4 6
9 4 6
4 2 4
5 5 1
6 5 6
8 7 5
9 7 6
7 5 6
8 4 6
8 3 6
8 6 6
9 6 6
7 7 6
6 5 4
6 4 4
9 5 5
6 6 0
7 4 4
7 7 4
7 5 2
7 5 6
7 2 3
8 3 5
8 6 4
4 5 5
7 5 6
7 2 4
7 2 6
7 5 3
5 2 5
4 3 3
6 4 5
9 8 5
4 4 4
4 2 5
3 3 5
8 5 5
3 4 5
8 5 4
9 5 6
8 8 5
8 6 5
7 5 6
8 9 6
8 2 4
7 3 5
5 6 4
7 2 6
7 3 4
4 1 4
6 2 2
6 1 5
6 1 4
6 2 4
4 5 3
5 6 2
3 6 6
8 2 4
7 2 4
6 4 3
4 5 1
4 2 5
8 1 6
4 1 4
8 1 5
6 5 4
4 0 3
7 4 5
8 5 6
4 3 5
5 7 5
9 6 5
2 2 1
6 5 4
6 6 6
4 3 4
5 2 3
3 2 5
6 6 5
8 6 5
8 3 5
4 3 4
7 4 5
5 1 6
3 1 4
9 3 6
5 2 6
5 3 4
9 5 6
8 1 4
4 4 5
9 3 2
4 2 2
5 2 2
6 3 5
4 4 4
3 3 6
3 4 5
8 3 6
6 1 5
9 2 6
9 3 5
8 1 6
8 9 6
4 3 2
8 4 5
8 6 6
8 1 4
8 4 6
7 5 6
5 3 3
9 3 6
6 2 4
9 5 6
7 2 5
8 2 4
8 5 6
6 2 5
8 5 6
7 4 2
8 4 6
5 0 3
6 2 6
6 0 4
6 3 5
5 1 3
6 2 6
6 2 4
8 3 4
4 2 3
8 1 3
5 4 3
6 5 5
5 1 5
5 4 5
9 7 4
5 1 2
7 4 6
7 3 4
7 4 4
9 4 5
6 5 4
7 3 3
4 4 6
7 3 5
4 1 1
7 4 3
3 5 3
5 2 3
7 4 4
8 5 4
9 7 6
9 8 6
6 4 5
7 5 2
2 1 0
5 2 3
6 0 5
7 6 5
6 1 4
8 4 5
9 4 6
6 2 3
3 4 5
9 3 6
8 2 1
6 1 4
6 3 4
8 6 1
5 2 2
9 8 6
8 6 6
6 1 5
8 5 5
6 3 6
7 4 6
4 4 4
7 2 5
4 0 1
6 4 5
8 5 5
'DELETED' "'DELETED'" "'DELETED'"
7 6 3
5 2 3
8 5 6
8 2 5
9 4 6
8 3 5
4 0 0
7 5 6
7 7 5
9 6 5
7 5 5
7 4 5
5 1 2
8 4 5
7 3 5
5 3 5
8 7 3
9 3 4
8 3 6
6 5 3
2 3 2
9 6 6
9 7 5
4 3 3
7 2 5
9 6 5
7 5 4
8 1 6
5 2 3
6 3 3
6 2 4
3 3 4
4 1 3
8 3 6
6 7 5
5 3 4
7 4 4
7 1 5
5 2 6
7 2 5
8 7 4
6 1 5
6 1 3
8 8 5
6 4 5
8 2 5
8 3 5
7 3 4
6 3 5
3 3 6
8 2 5
8 4 5
8 5 6
7 5 4
5 2 4
5 2 3

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261730&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261730&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261730&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'George Udny Yule' @ yule.wessa.net






ANOVA Model
Calculation ~ Algebraic_Reasoning
means3.6152.3264.7182.5792.8033.2293.513.7574.3294.3854.135

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Calculation  ~  Algebraic_Reasoning \tabularnewline
means & 3.615 & 2.326 & 4.718 & 2.579 & 2.803 & 3.229 & 3.51 & 3.757 & 4.329 & 4.385 & 4.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261730&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Calculation  ~  Algebraic_Reasoning[/C][/ROW]
[ROW][C]means[/C][C]3.615[/C][C]2.326[/C][C]4.718[/C][C]2.579[/C][C]2.803[/C][C]3.229[/C][C]3.51[/C][C]3.757[/C][C]4.329[/C][C]4.385[/C][C]4.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261730&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261730&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
Calculation ~ Algebraic_Reasoning
means3.6152.3264.7182.5792.8033.2293.513.7574.3294.3854.135






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Algebraic_Reasoning10372.17937.21815.9070
Residuals7191682.2272.34 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Algebraic_Reasoning & 10 & 372.179 & 37.218 & 15.907 & 0 \tabularnewline
Residuals & 719 & 1682.227 & 2.34 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261730&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]Algebraic_Reasoning[/C][C]10[/C][C]372.179[/C][C]37.218[/C][C]15.907[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]719[/C][C]1682.227[/C][C]2.34[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261730&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261730&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)
Algebraic_Reasoning10372.17937.21815.9070
Residuals7191682.2272.34






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-02.3260.7153.9360
10-04.7181.5547.8820
2-02.5791.0984.060
3-02.8031.3594.2470
4-03.2291.8054.6530
5-03.512.0794.940
6-03.7572.2875.2270
7-04.3292.8035.8550
8-04.3852.7366.0330
9-04.1352.1576.1120
10-12.392-0.5835.3670.252
2-10.254-0.7631.2710.999
3-10.478-0.4851.440.881
4-10.904-0.0291.8360.067
5-11.1840.2422.1260.003
6-11.4310.432.4320
7-12.0030.9223.0850
8-12.0590.813.3070
9-11.8090.153.4670.02
2-10-2.139-5.0450.7680.384
3-10-1.915-4.8030.9730.548
4-10-1.489-4.3671.390.85
5-10-1.208-4.091.6730.959
6-10-0.961-3.8621.940.993
7-10-0.389-3.3192.5411
8-10-0.333-3.3292.6621
9-10-0.583-3.7722.6051
3-20.224-0.5010.9490.996
4-20.65-0.0341.3340.08
5-20.930.2331.6280.001
6-21.1770.4021.9520
7-21.750.8732.6260
8-21.8050.7292.8810
9-21.5550.0223.0880.043
4-30.426-0.1741.0260.44
5-30.7060.0911.3210.01
6-30.9530.2521.6550.001
7-31.5260.7132.3380
8-31.5810.5572.6060
9-31.331-0.1662.8280.134
5-40.28-0.2860.8470.883
6-40.527-0.1321.1870.26
7-41.10.3231.8760
8-41.1550.1592.1520.009
9-40.905-0.5732.3830.665
6-50.247-0.4260.920.984
7-50.8190.0311.6080.034
8-50.875-0.131.880.156
9-50.625-0.8592.1090.957
7-60.572-0.2851.430.538
8-60.628-0.4331.6890.71
9-60.378-1.1441.90.999
8-70.056-1.0821.1931
9-7-0.194-1.7711.3821
9-8-0.25-1.9451.4451

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 2.326 & 0.715 & 3.936 & 0 \tabularnewline
10-0 & 4.718 & 1.554 & 7.882 & 0 \tabularnewline
2-0 & 2.579 & 1.098 & 4.06 & 0 \tabularnewline
3-0 & 2.803 & 1.359 & 4.247 & 0 \tabularnewline
4-0 & 3.229 & 1.805 & 4.653 & 0 \tabularnewline
5-0 & 3.51 & 2.079 & 4.94 & 0 \tabularnewline
6-0 & 3.757 & 2.287 & 5.227 & 0 \tabularnewline
7-0 & 4.329 & 2.803 & 5.855 & 0 \tabularnewline
8-0 & 4.385 & 2.736 & 6.033 & 0 \tabularnewline
9-0 & 4.135 & 2.157 & 6.112 & 0 \tabularnewline
10-1 & 2.392 & -0.583 & 5.367 & 0.252 \tabularnewline
2-1 & 0.254 & -0.763 & 1.271 & 0.999 \tabularnewline
3-1 & 0.478 & -0.485 & 1.44 & 0.881 \tabularnewline
4-1 & 0.904 & -0.029 & 1.836 & 0.067 \tabularnewline
5-1 & 1.184 & 0.242 & 2.126 & 0.003 \tabularnewline
6-1 & 1.431 & 0.43 & 2.432 & 0 \tabularnewline
7-1 & 2.003 & 0.922 & 3.085 & 0 \tabularnewline
8-1 & 2.059 & 0.81 & 3.307 & 0 \tabularnewline
9-1 & 1.809 & 0.15 & 3.467 & 0.02 \tabularnewline
2-10 & -2.139 & -5.045 & 0.768 & 0.384 \tabularnewline
3-10 & -1.915 & -4.803 & 0.973 & 0.548 \tabularnewline
4-10 & -1.489 & -4.367 & 1.39 & 0.85 \tabularnewline
5-10 & -1.208 & -4.09 & 1.673 & 0.959 \tabularnewline
6-10 & -0.961 & -3.862 & 1.94 & 0.993 \tabularnewline
7-10 & -0.389 & -3.319 & 2.541 & 1 \tabularnewline
8-10 & -0.333 & -3.329 & 2.662 & 1 \tabularnewline
9-10 & -0.583 & -3.772 & 2.605 & 1 \tabularnewline
3-2 & 0.224 & -0.501 & 0.949 & 0.996 \tabularnewline
4-2 & 0.65 & -0.034 & 1.334 & 0.08 \tabularnewline
5-2 & 0.93 & 0.233 & 1.628 & 0.001 \tabularnewline
6-2 & 1.177 & 0.402 & 1.952 & 0 \tabularnewline
7-2 & 1.75 & 0.873 & 2.626 & 0 \tabularnewline
8-2 & 1.805 & 0.729 & 2.881 & 0 \tabularnewline
9-2 & 1.555 & 0.022 & 3.088 & 0.043 \tabularnewline
4-3 & 0.426 & -0.174 & 1.026 & 0.44 \tabularnewline
5-3 & 0.706 & 0.091 & 1.321 & 0.01 \tabularnewline
6-3 & 0.953 & 0.252 & 1.655 & 0.001 \tabularnewline
7-3 & 1.526 & 0.713 & 2.338 & 0 \tabularnewline
8-3 & 1.581 & 0.557 & 2.606 & 0 \tabularnewline
9-3 & 1.331 & -0.166 & 2.828 & 0.134 \tabularnewline
5-4 & 0.28 & -0.286 & 0.847 & 0.883 \tabularnewline
6-4 & 0.527 & -0.132 & 1.187 & 0.26 \tabularnewline
7-4 & 1.1 & 0.323 & 1.876 & 0 \tabularnewline
8-4 & 1.155 & 0.159 & 2.152 & 0.009 \tabularnewline
9-4 & 0.905 & -0.573 & 2.383 & 0.665 \tabularnewline
6-5 & 0.247 & -0.426 & 0.92 & 0.984 \tabularnewline
7-5 & 0.819 & 0.031 & 1.608 & 0.034 \tabularnewline
8-5 & 0.875 & -0.13 & 1.88 & 0.156 \tabularnewline
9-5 & 0.625 & -0.859 & 2.109 & 0.957 \tabularnewline
7-6 & 0.572 & -0.285 & 1.43 & 0.538 \tabularnewline
8-6 & 0.628 & -0.433 & 1.689 & 0.71 \tabularnewline
9-6 & 0.378 & -1.144 & 1.9 & 0.999 \tabularnewline
8-7 & 0.056 & -1.082 & 1.193 & 1 \tabularnewline
9-7 & -0.194 & -1.771 & 1.382 & 1 \tabularnewline
9-8 & -0.25 & -1.945 & 1.445 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261730&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]2.326[/C][C]0.715[/C][C]3.936[/C][C]0[/C][/ROW]
[ROW][C]10-0[/C][C]4.718[/C][C]1.554[/C][C]7.882[/C][C]0[/C][/ROW]
[ROW][C]2-0[/C][C]2.579[/C][C]1.098[/C][C]4.06[/C][C]0[/C][/ROW]
[ROW][C]3-0[/C][C]2.803[/C][C]1.359[/C][C]4.247[/C][C]0[/C][/ROW]
[ROW][C]4-0[/C][C]3.229[/C][C]1.805[/C][C]4.653[/C][C]0[/C][/ROW]
[ROW][C]5-0[/C][C]3.51[/C][C]2.079[/C][C]4.94[/C][C]0[/C][/ROW]
[ROW][C]6-0[/C][C]3.757[/C][C]2.287[/C][C]5.227[/C][C]0[/C][/ROW]
[ROW][C]7-0[/C][C]4.329[/C][C]2.803[/C][C]5.855[/C][C]0[/C][/ROW]
[ROW][C]8-0[/C][C]4.385[/C][C]2.736[/C][C]6.033[/C][C]0[/C][/ROW]
[ROW][C]9-0[/C][C]4.135[/C][C]2.157[/C][C]6.112[/C][C]0[/C][/ROW]
[ROW][C]10-1[/C][C]2.392[/C][C]-0.583[/C][C]5.367[/C][C]0.252[/C][/ROW]
[ROW][C]2-1[/C][C]0.254[/C][C]-0.763[/C][C]1.271[/C][C]0.999[/C][/ROW]
[ROW][C]3-1[/C][C]0.478[/C][C]-0.485[/C][C]1.44[/C][C]0.881[/C][/ROW]
[ROW][C]4-1[/C][C]0.904[/C][C]-0.029[/C][C]1.836[/C][C]0.067[/C][/ROW]
[ROW][C]5-1[/C][C]1.184[/C][C]0.242[/C][C]2.126[/C][C]0.003[/C][/ROW]
[ROW][C]6-1[/C][C]1.431[/C][C]0.43[/C][C]2.432[/C][C]0[/C][/ROW]
[ROW][C]7-1[/C][C]2.003[/C][C]0.922[/C][C]3.085[/C][C]0[/C][/ROW]
[ROW][C]8-1[/C][C]2.059[/C][C]0.81[/C][C]3.307[/C][C]0[/C][/ROW]
[ROW][C]9-1[/C][C]1.809[/C][C]0.15[/C][C]3.467[/C][C]0.02[/C][/ROW]
[ROW][C]2-10[/C][C]-2.139[/C][C]-5.045[/C][C]0.768[/C][C]0.384[/C][/ROW]
[ROW][C]3-10[/C][C]-1.915[/C][C]-4.803[/C][C]0.973[/C][C]0.548[/C][/ROW]
[ROW][C]4-10[/C][C]-1.489[/C][C]-4.367[/C][C]1.39[/C][C]0.85[/C][/ROW]
[ROW][C]5-10[/C][C]-1.208[/C][C]-4.09[/C][C]1.673[/C][C]0.959[/C][/ROW]
[ROW][C]6-10[/C][C]-0.961[/C][C]-3.862[/C][C]1.94[/C][C]0.993[/C][/ROW]
[ROW][C]7-10[/C][C]-0.389[/C][C]-3.319[/C][C]2.541[/C][C]1[/C][/ROW]
[ROW][C]8-10[/C][C]-0.333[/C][C]-3.329[/C][C]2.662[/C][C]1[/C][/ROW]
[ROW][C]9-10[/C][C]-0.583[/C][C]-3.772[/C][C]2.605[/C][C]1[/C][/ROW]
[ROW][C]3-2[/C][C]0.224[/C][C]-0.501[/C][C]0.949[/C][C]0.996[/C][/ROW]
[ROW][C]4-2[/C][C]0.65[/C][C]-0.034[/C][C]1.334[/C][C]0.08[/C][/ROW]
[ROW][C]5-2[/C][C]0.93[/C][C]0.233[/C][C]1.628[/C][C]0.001[/C][/ROW]
[ROW][C]6-2[/C][C]1.177[/C][C]0.402[/C][C]1.952[/C][C]0[/C][/ROW]
[ROW][C]7-2[/C][C]1.75[/C][C]0.873[/C][C]2.626[/C][C]0[/C][/ROW]
[ROW][C]8-2[/C][C]1.805[/C][C]0.729[/C][C]2.881[/C][C]0[/C][/ROW]
[ROW][C]9-2[/C][C]1.555[/C][C]0.022[/C][C]3.088[/C][C]0.043[/C][/ROW]
[ROW][C]4-3[/C][C]0.426[/C][C]-0.174[/C][C]1.026[/C][C]0.44[/C][/ROW]
[ROW][C]5-3[/C][C]0.706[/C][C]0.091[/C][C]1.321[/C][C]0.01[/C][/ROW]
[ROW][C]6-3[/C][C]0.953[/C][C]0.252[/C][C]1.655[/C][C]0.001[/C][/ROW]
[ROW][C]7-3[/C][C]1.526[/C][C]0.713[/C][C]2.338[/C][C]0[/C][/ROW]
[ROW][C]8-3[/C][C]1.581[/C][C]0.557[/C][C]2.606[/C][C]0[/C][/ROW]
[ROW][C]9-3[/C][C]1.331[/C][C]-0.166[/C][C]2.828[/C][C]0.134[/C][/ROW]
[ROW][C]5-4[/C][C]0.28[/C][C]-0.286[/C][C]0.847[/C][C]0.883[/C][/ROW]
[ROW][C]6-4[/C][C]0.527[/C][C]-0.132[/C][C]1.187[/C][C]0.26[/C][/ROW]
[ROW][C]7-4[/C][C]1.1[/C][C]0.323[/C][C]1.876[/C][C]0[/C][/ROW]
[ROW][C]8-4[/C][C]1.155[/C][C]0.159[/C][C]2.152[/C][C]0.009[/C][/ROW]
[ROW][C]9-4[/C][C]0.905[/C][C]-0.573[/C][C]2.383[/C][C]0.665[/C][/ROW]
[ROW][C]6-5[/C][C]0.247[/C][C]-0.426[/C][C]0.92[/C][C]0.984[/C][/ROW]
[ROW][C]7-5[/C][C]0.819[/C][C]0.031[/C][C]1.608[/C][C]0.034[/C][/ROW]
[ROW][C]8-5[/C][C]0.875[/C][C]-0.13[/C][C]1.88[/C][C]0.156[/C][/ROW]
[ROW][C]9-5[/C][C]0.625[/C][C]-0.859[/C][C]2.109[/C][C]0.957[/C][/ROW]
[ROW][C]7-6[/C][C]0.572[/C][C]-0.285[/C][C]1.43[/C][C]0.538[/C][/ROW]
[ROW][C]8-6[/C][C]0.628[/C][C]-0.433[/C][C]1.689[/C][C]0.71[/C][/ROW]
[ROW][C]9-6[/C][C]0.378[/C][C]-1.144[/C][C]1.9[/C][C]0.999[/C][/ROW]
[ROW][C]8-7[/C][C]0.056[/C][C]-1.082[/C][C]1.193[/C][C]1[/C][/ROW]
[ROW][C]9-7[/C][C]-0.194[/C][C]-1.771[/C][C]1.382[/C][C]1[/C][/ROW]
[ROW][C]9-8[/C][C]-0.25[/C][C]-1.945[/C][C]1.445[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261730&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261730&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
1-02.3260.7153.9360
10-04.7181.5547.8820
2-02.5791.0984.060
3-02.8031.3594.2470
4-03.2291.8054.6530
5-03.512.0794.940
6-03.7572.2875.2270
7-04.3292.8035.8550
8-04.3852.7366.0330
9-04.1352.1576.1120
10-12.392-0.5835.3670.252
2-10.254-0.7631.2710.999
3-10.478-0.4851.440.881
4-10.904-0.0291.8360.067
5-11.1840.2422.1260.003
6-11.4310.432.4320
7-12.0030.9223.0850
8-12.0590.813.3070
9-11.8090.153.4670.02
2-10-2.139-5.0450.7680.384
3-10-1.915-4.8030.9730.548
4-10-1.489-4.3671.390.85
5-10-1.208-4.091.6730.959
6-10-0.961-3.8621.940.993
7-10-0.389-3.3192.5411
8-10-0.333-3.3292.6621
9-10-0.583-3.7722.6051
3-20.224-0.5010.9490.996
4-20.65-0.0341.3340.08
5-20.930.2331.6280.001
6-21.1770.4021.9520
7-21.750.8732.6260
8-21.8050.7292.8810
9-21.5550.0223.0880.043
4-30.426-0.1741.0260.44
5-30.7060.0911.3210.01
6-30.9530.2521.6550.001
7-31.5260.7132.3380
8-31.5810.5572.6060
9-31.331-0.1662.8280.134
5-40.28-0.2860.8470.883
6-40.527-0.1321.1870.26
7-41.10.3231.8760
8-41.1550.1592.1520.009
9-40.905-0.5732.3830.665
6-50.247-0.4260.920.984
7-50.8190.0311.6080.034
8-50.875-0.131.880.156
9-50.625-0.8592.1090.957
7-60.572-0.2851.430.538
8-60.628-0.4331.6890.71
9-60.378-1.1441.90.999
8-70.056-1.0821.1931
9-7-0.194-1.7711.3821
9-8-0.25-1.9451.4451






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group103.790
719 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 10 & 3.79 & 0 \tabularnewline
  & 719 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261730&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]10[/C][C]3.79[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]719[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261730&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261730&T=4

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


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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group103.790
719


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, 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$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$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)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], 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, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
'Tukey Plot'
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
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(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
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<-leveneTest(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')