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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationSun, 10 Nov 2013 18:21:21 -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/2013/Nov/10/t1384125711nntsj5z98ckbncw.htm/, Retrieved Tue, 07 May 2024 14:02:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=223811, Retrieved Tue, 07 May 2024 14:02:09 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA wit...] [2009-11-29 13:09:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA for...] [2009-12-01 13:05:10] [3fdd735c61ad38cbc9b3393dc997cdb7]
- R P     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [CARE date with Tu...] [2009-12-01 18:33:48] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE Data with Tu...] [2010-11-23 12:09:38] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IQ and Mothers Age] [2011-11-21 16:34:08] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R  D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-10 23:21:21] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
67	3
86	6
86	8
103	8
74	7
63	5
82	7
93	8
77	9
111	9
71	3
103	9
89	7
75	9
88	8
84	6
85	7
70	8
104	9
88	7
77	6
77	8
72	7
70	7
83	8
110	9
91	9
80	7
91	4
86	7
85	7
107	9
93	7
87	9
84	10
73	5
84	6
86	9
99	9
75	8
87	6
79	6
82	5
95	8
84	8
85	5
95	6
63	9
78	8
85	4
86	8
75	9
98	7
71	7
63	6
71	9
84	9
81	8
93	4
79	6
63	10
93	8
92	7
93	7
83	8
80	3
111	8
92	10
79	7
69	5
83	10
80	5
91	8
97	9
85	6
85	9
99	8
67	5
87	8
68	3
81	7
80	8
93	10
93	9
102	10
104	9
90	8
85	8
92	8
82	9
85	4
89	6
77	7
79	4
76	9
101	7
81	8
89	8
81	7
77	7
95	9
85	8
81	8
76	9
93	9
104	10
89	7
76	8
77	5
71	9
79	8
89	7
81	8
99	8
81	7
84	6
85	7
111	7
78	6
111	6
78	7
87	9
92	6
93	10
70	4
84	8
75	7
105	10
85	5
87	9
75	8
103	9
86	8
77	8
74	9
74	8
76	9
83	7
101	6
83	8
92	6
74	5
87	3
71	6
79	8
83	7
80	8
90	6
80	9
96	9
109	10
98	7
85	5
83	8
86	9
72	8
83	8
75	4

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'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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223811&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223811&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223811&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'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
MVRBIQ0 ~ MWARM30
means92.8-18.2-10.229-16.436-7.168-8.09-8.11-4.8

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MVRBIQ0  ~  MWARM30 \tabularnewline
means & 92.8 & -18.2 & -10.229 & -16.436 & -7.168 & -8.09 & -8.11 & -4.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223811&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MVRBIQ0  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]92.8[/C][C]-18.2[/C][C]-10.229[/C][C]-16.436[/C][C]-7.168[/C][C]-8.09[/C][C]-8.11[/C][C]-4.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223811&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223811&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
MVRBIQ0 ~ MWARM30
means92.8-18.2-10.229-16.436-7.168-8.09-8.11-4.8






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM3072322.099331.7283.1620.004
Residuals15015734.844104.899 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 7 & 2322.099 & 331.728 & 3.162 & 0.004 \tabularnewline
Residuals & 150 & 15734.844 & 104.899 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223811&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]MWARM30[/C][C]7[/C][C]2322.099[/C][C]331.728[/C][C]3.162[/C][C]0.004[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]15734.844[/C][C]104.899[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223811&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223811&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)
MWARM3072322.099331.7283.1620.004
Residuals15015734.844104.899






Tukey Honest Significant Difference Comparisons
difflwruprp adj
3-10-18.2-35.446-0.9540.031
4-10-10.229-25.7455.2880.468
5-10-16.436-30.194-2.6790.008
6-10-7.168-19.4695.1330.627
7-10-8.09-19.5413.360.375
8-10-8.11-19.1882.9690.328
9-10-4.8-16.1666.5660.898
4-37.971-10.46526.4080.886
5-31.764-15.21918.7461
6-311.032-4.79426.8570.393
7-310.11-5.06425.2840.453
8-310.09-4.80524.9860.431
9-313.4-1.7128.510.123
5-4-6.208-21.4319.0150.914
6-43.06-10.86116.9810.998
7-42.138-11.03815.3141
8-42.119-10.73514.9731
9-45.429-7.67418.5310.907
6-59.268-2.66121.1970.255
7-58.346-2.70419.3960.289
8-58.327-2.33718.9910.249
9-511.6360.67422.5980.029
7-6-0.922-10.0968.2521
8-6-0.941-9.6467.7641
9-62.368-6.69911.4360.993
8-7-0.019-7.4757.4361
9-73.29-4.58511.1660.903
9-83.31-4.01510.6340.861

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
3-10 & -18.2 & -35.446 & -0.954 & 0.031 \tabularnewline
4-10 & -10.229 & -25.745 & 5.288 & 0.468 \tabularnewline
5-10 & -16.436 & -30.194 & -2.679 & 0.008 \tabularnewline
6-10 & -7.168 & -19.469 & 5.133 & 0.627 \tabularnewline
7-10 & -8.09 & -19.541 & 3.36 & 0.375 \tabularnewline
8-10 & -8.11 & -19.188 & 2.969 & 0.328 \tabularnewline
9-10 & -4.8 & -16.166 & 6.566 & 0.898 \tabularnewline
4-3 & 7.971 & -10.465 & 26.408 & 0.886 \tabularnewline
5-3 & 1.764 & -15.219 & 18.746 & 1 \tabularnewline
6-3 & 11.032 & -4.794 & 26.857 & 0.393 \tabularnewline
7-3 & 10.11 & -5.064 & 25.284 & 0.453 \tabularnewline
8-3 & 10.09 & -4.805 & 24.986 & 0.431 \tabularnewline
9-3 & 13.4 & -1.71 & 28.51 & 0.123 \tabularnewline
5-4 & -6.208 & -21.431 & 9.015 & 0.914 \tabularnewline
6-4 & 3.06 & -10.861 & 16.981 & 0.998 \tabularnewline
7-4 & 2.138 & -11.038 & 15.314 & 1 \tabularnewline
8-4 & 2.119 & -10.735 & 14.973 & 1 \tabularnewline
9-4 & 5.429 & -7.674 & 18.531 & 0.907 \tabularnewline
6-5 & 9.268 & -2.661 & 21.197 & 0.255 \tabularnewline
7-5 & 8.346 & -2.704 & 19.396 & 0.289 \tabularnewline
8-5 & 8.327 & -2.337 & 18.991 & 0.249 \tabularnewline
9-5 & 11.636 & 0.674 & 22.598 & 0.029 \tabularnewline
7-6 & -0.922 & -10.096 & 8.252 & 1 \tabularnewline
8-6 & -0.941 & -9.646 & 7.764 & 1 \tabularnewline
9-6 & 2.368 & -6.699 & 11.436 & 0.993 \tabularnewline
8-7 & -0.019 & -7.475 & 7.436 & 1 \tabularnewline
9-7 & 3.29 & -4.585 & 11.166 & 0.903 \tabularnewline
9-8 & 3.31 & -4.015 & 10.634 & 0.861 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223811&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]3-10[/C][C]-18.2[/C][C]-35.446[/C][C]-0.954[/C][C]0.031[/C][/ROW]
[ROW][C]4-10[/C][C]-10.229[/C][C]-25.745[/C][C]5.288[/C][C]0.468[/C][/ROW]
[ROW][C]5-10[/C][C]-16.436[/C][C]-30.194[/C][C]-2.679[/C][C]0.008[/C][/ROW]
[ROW][C]6-10[/C][C]-7.168[/C][C]-19.469[/C][C]5.133[/C][C]0.627[/C][/ROW]
[ROW][C]7-10[/C][C]-8.09[/C][C]-19.541[/C][C]3.36[/C][C]0.375[/C][/ROW]
[ROW][C]8-10[/C][C]-8.11[/C][C]-19.188[/C][C]2.969[/C][C]0.328[/C][/ROW]
[ROW][C]9-10[/C][C]-4.8[/C][C]-16.166[/C][C]6.566[/C][C]0.898[/C][/ROW]
[ROW][C]4-3[/C][C]7.971[/C][C]-10.465[/C][C]26.408[/C][C]0.886[/C][/ROW]
[ROW][C]5-3[/C][C]1.764[/C][C]-15.219[/C][C]18.746[/C][C]1[/C][/ROW]
[ROW][C]6-3[/C][C]11.032[/C][C]-4.794[/C][C]26.857[/C][C]0.393[/C][/ROW]
[ROW][C]7-3[/C][C]10.11[/C][C]-5.064[/C][C]25.284[/C][C]0.453[/C][/ROW]
[ROW][C]8-3[/C][C]10.09[/C][C]-4.805[/C][C]24.986[/C][C]0.431[/C][/ROW]
[ROW][C]9-3[/C][C]13.4[/C][C]-1.71[/C][C]28.51[/C][C]0.123[/C][/ROW]
[ROW][C]5-4[/C][C]-6.208[/C][C]-21.431[/C][C]9.015[/C][C]0.914[/C][/ROW]
[ROW][C]6-4[/C][C]3.06[/C][C]-10.861[/C][C]16.981[/C][C]0.998[/C][/ROW]
[ROW][C]7-4[/C][C]2.138[/C][C]-11.038[/C][C]15.314[/C][C]1[/C][/ROW]
[ROW][C]8-4[/C][C]2.119[/C][C]-10.735[/C][C]14.973[/C][C]1[/C][/ROW]
[ROW][C]9-4[/C][C]5.429[/C][C]-7.674[/C][C]18.531[/C][C]0.907[/C][/ROW]
[ROW][C]6-5[/C][C]9.268[/C][C]-2.661[/C][C]21.197[/C][C]0.255[/C][/ROW]
[ROW][C]7-5[/C][C]8.346[/C][C]-2.704[/C][C]19.396[/C][C]0.289[/C][/ROW]
[ROW][C]8-5[/C][C]8.327[/C][C]-2.337[/C][C]18.991[/C][C]0.249[/C][/ROW]
[ROW][C]9-5[/C][C]11.636[/C][C]0.674[/C][C]22.598[/C][C]0.029[/C][/ROW]
[ROW][C]7-6[/C][C]-0.922[/C][C]-10.096[/C][C]8.252[/C][C]1[/C][/ROW]
[ROW][C]8-6[/C][C]-0.941[/C][C]-9.646[/C][C]7.764[/C][C]1[/C][/ROW]
[ROW][C]9-6[/C][C]2.368[/C][C]-6.699[/C][C]11.436[/C][C]0.993[/C][/ROW]
[ROW][C]8-7[/C][C]-0.019[/C][C]-7.475[/C][C]7.436[/C][C]1[/C][/ROW]
[ROW][C]9-7[/C][C]3.29[/C][C]-4.585[/C][C]11.166[/C][C]0.903[/C][/ROW]
[ROW][C]9-8[/C][C]3.31[/C][C]-4.015[/C][C]10.634[/C][C]0.861[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223811&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223811&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
3-10-18.2-35.446-0.9540.031
4-10-10.229-25.7455.2880.468
5-10-16.436-30.194-2.6790.008
6-10-7.168-19.4695.1330.627
7-10-8.09-19.5413.360.375
8-10-8.11-19.1882.9690.328
9-10-4.8-16.1666.5660.898
4-37.971-10.46526.4080.886
5-31.764-15.21918.7461
6-311.032-4.79426.8570.393
7-310.11-5.06425.2840.453
8-310.09-4.80524.9860.431
9-313.4-1.7128.510.123
5-4-6.208-21.4319.0150.914
6-43.06-10.86116.9810.998
7-42.138-11.03815.3141
8-42.119-10.73514.9731
9-45.429-7.67418.5310.907
6-59.268-2.66121.1970.255
7-58.346-2.70419.3960.289
8-58.327-2.33718.9910.249
9-511.6360.67422.5980.029
7-6-0.922-10.0968.2521
8-6-0.941-9.6467.7641
9-62.368-6.69911.4360.993
8-7-0.019-7.4757.4361
9-73.29-4.58511.1660.903
9-83.31-4.01510.6340.861






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group71.4340.196
150 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 7 & 1.434 & 0.196 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223811&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]7[/C][C]1.434[/C][C]0.196[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223811&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223811&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)
Group71.4340.196
150


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){
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<-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')