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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, 28 Nov 2011 09:56:15 -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/2011/Nov/28/t1322492218mbtinkjg1wrgljy.htm/, Retrieved Fri, 26 Apr 2024 13:55:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147783, Retrieved Fri, 26 Apr 2024 13:55:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

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)] [question 1 (30)] [2011-11-28 14:56:15] [801b48c24a3853d6e994f3c4a732a401] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3	3
1	6
3	8
3	8
3	7
1	5
2	7
3	8
3	9
2	9
1	3
1	9
3	7
3	9
3	8
1	6
3	7
3	8
3	9
2	7
2	6
1	8
1	7
3	7
3	8
1	9
1	9
3	7
1	4
2	7
3	7
2	9
2	7
3	9
1	10
3	5
3	6
1	9
2	9
1	8
1	6
2	6
1	5
1	8
3	8
2	5
2	6
1	9
1	8
1	4
1	8
2	9
3	7
3	7
3	6
3	9
2	9
2	8
2	4
3	6
3	10
2	8
2	7
2	7
3	8
2	3
3	8
3	10
2	7
2	5
3	10
3	5
2	8
1	9
2	6
2	9
2	8
2	5
3	8
2	3
3	7
1	8
3	10
3	9
1	10
1	9
2	8
1	8
3	8
1	9
3	4
2	6
3	7
1	4
1	9
2	7
3	8
3	8
1	7
2	7
2	9
3	8
3	8
1	9
3	9
3	10
3	7
2	8
3	5
3	9
3	8
3	7
1	8
3	8
1	7
3	6
3	7
3	7
2	6
3	6
2	7
3	9
2	6
2	10
2	4
3	8
3	7
1	10
3	5
3	9
2	8
1	9
3	8
3	8
3	9
2	8
1	9
3	7
3	6
3	8
2	6
3	5
2	3
3	6
3	8
2	7
3	8
3	6
3	9
3	9
1	10
3	7
2	5
3	8
3	9
1	8
1	8
3	4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147783&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147783&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147783&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
MC30VRB ~ MOMAGE
means2.1-0.1-0.2430.1730.1630.3520.233-0.039

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MOMAGE \tabularnewline
means & 2.1 & -0.1 & -0.243 & 0.173 & 0.163 & 0.352 & 0.233 & -0.039 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147783&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MOMAGE[/C][/ROW]
[ROW][C]means[/C][C]2.1[/C][C]-0.1[/C][C]-0.243[/C][C]0.173[/C][C]0.163[/C][C]0.352[/C][C]0.233[/C][C]-0.039[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147783&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147783&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
MC30VRB ~ MOMAGE
means2.1-0.1-0.2430.1730.1630.3520.233-0.039






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MOMAGE74.3480.6210.9270.487
Residuals150100.5130.67 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MOMAGE & 7 & 4.348 & 0.621 & 0.927 & 0.487 \tabularnewline
Residuals & 150 & 100.513 & 0.67 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147783&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]MOMAGE[/C][C]7[/C][C]4.348[/C][C]0.621[/C][C]0.927[/C][C]0.487[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]100.513[/C][C]0.67[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147783&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147783&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)
MOMAGE74.3480.6210.9270.487
Residuals150100.5130.67






Tukey Honest Significant Difference Comparisons
difflwruprp adj
3-10-0.1-1.4781.2781
4-10-0.243-1.4830.9970.999
5-100.173-0.9271.2721
6-100.163-0.821.1461
7-100.352-0.5641.2670.936
8-100.233-0.6521.1190.992
9-10-0.039-0.9480.8691
4-3-0.143-1.6161.3311
5-30.273-1.0851.630.999
6-30.263-1.0021.5280.998
7-30.452-0.7611.6640.946
8-30.333-0.8571.5240.989
9-30.061-1.1471.2681
5-40.416-0.8011.6320.966
6-40.406-0.7071.5190.951
7-40.594-0.4591.6480.664
8-40.476-0.5511.5040.844
9-40.203-0.8441.2510.999
6-5-0.01-0.9630.9441
7-50.179-0.7041.0620.999
8-50.061-0.7920.9131
9-5-0.212-1.0880.6640.995
7-60.188-0.5450.9220.993
8-60.07-0.6260.7661
9-6-0.203-0.9270.5220.989
8-7-0.118-0.7140.4780.999
9-7-0.391-1.020.2380.546
9-8-0.273-0.8580.3130.841

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
3-10 & -0.1 & -1.478 & 1.278 & 1 \tabularnewline
4-10 & -0.243 & -1.483 & 0.997 & 0.999 \tabularnewline
5-10 & 0.173 & -0.927 & 1.272 & 1 \tabularnewline
6-10 & 0.163 & -0.82 & 1.146 & 1 \tabularnewline
7-10 & 0.352 & -0.564 & 1.267 & 0.936 \tabularnewline
8-10 & 0.233 & -0.652 & 1.119 & 0.992 \tabularnewline
9-10 & -0.039 & -0.948 & 0.869 & 1 \tabularnewline
4-3 & -0.143 & -1.616 & 1.331 & 1 \tabularnewline
5-3 & 0.273 & -1.085 & 1.63 & 0.999 \tabularnewline
6-3 & 0.263 & -1.002 & 1.528 & 0.998 \tabularnewline
7-3 & 0.452 & -0.761 & 1.664 & 0.946 \tabularnewline
8-3 & 0.333 & -0.857 & 1.524 & 0.989 \tabularnewline
9-3 & 0.061 & -1.147 & 1.268 & 1 \tabularnewline
5-4 & 0.416 & -0.801 & 1.632 & 0.966 \tabularnewline
6-4 & 0.406 & -0.707 & 1.519 & 0.951 \tabularnewline
7-4 & 0.594 & -0.459 & 1.648 & 0.664 \tabularnewline
8-4 & 0.476 & -0.551 & 1.504 & 0.844 \tabularnewline
9-4 & 0.203 & -0.844 & 1.251 & 0.999 \tabularnewline
6-5 & -0.01 & -0.963 & 0.944 & 1 \tabularnewline
7-5 & 0.179 & -0.704 & 1.062 & 0.999 \tabularnewline
8-5 & 0.061 & -0.792 & 0.913 & 1 \tabularnewline
9-5 & -0.212 & -1.088 & 0.664 & 0.995 \tabularnewline
7-6 & 0.188 & -0.545 & 0.922 & 0.993 \tabularnewline
8-6 & 0.07 & -0.626 & 0.766 & 1 \tabularnewline
9-6 & -0.203 & -0.927 & 0.522 & 0.989 \tabularnewline
8-7 & -0.118 & -0.714 & 0.478 & 0.999 \tabularnewline
9-7 & -0.391 & -1.02 & 0.238 & 0.546 \tabularnewline
9-8 & -0.273 & -0.858 & 0.313 & 0.841 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147783&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]-0.1[/C][C]-1.478[/C][C]1.278[/C][C]1[/C][/ROW]
[ROW][C]4-10[/C][C]-0.243[/C][C]-1.483[/C][C]0.997[/C][C]0.999[/C][/ROW]
[ROW][C]5-10[/C][C]0.173[/C][C]-0.927[/C][C]1.272[/C][C]1[/C][/ROW]
[ROW][C]6-10[/C][C]0.163[/C][C]-0.82[/C][C]1.146[/C][C]1[/C][/ROW]
[ROW][C]7-10[/C][C]0.352[/C][C]-0.564[/C][C]1.267[/C][C]0.936[/C][/ROW]
[ROW][C]8-10[/C][C]0.233[/C][C]-0.652[/C][C]1.119[/C][C]0.992[/C][/ROW]
[ROW][C]9-10[/C][C]-0.039[/C][C]-0.948[/C][C]0.869[/C][C]1[/C][/ROW]
[ROW][C]4-3[/C][C]-0.143[/C][C]-1.616[/C][C]1.331[/C][C]1[/C][/ROW]
[ROW][C]5-3[/C][C]0.273[/C][C]-1.085[/C][C]1.63[/C][C]0.999[/C][/ROW]
[ROW][C]6-3[/C][C]0.263[/C][C]-1.002[/C][C]1.528[/C][C]0.998[/C][/ROW]
[ROW][C]7-3[/C][C]0.452[/C][C]-0.761[/C][C]1.664[/C][C]0.946[/C][/ROW]
[ROW][C]8-3[/C][C]0.333[/C][C]-0.857[/C][C]1.524[/C][C]0.989[/C][/ROW]
[ROW][C]9-3[/C][C]0.061[/C][C]-1.147[/C][C]1.268[/C][C]1[/C][/ROW]
[ROW][C]5-4[/C][C]0.416[/C][C]-0.801[/C][C]1.632[/C][C]0.966[/C][/ROW]
[ROW][C]6-4[/C][C]0.406[/C][C]-0.707[/C][C]1.519[/C][C]0.951[/C][/ROW]
[ROW][C]7-4[/C][C]0.594[/C][C]-0.459[/C][C]1.648[/C][C]0.664[/C][/ROW]
[ROW][C]8-4[/C][C]0.476[/C][C]-0.551[/C][C]1.504[/C][C]0.844[/C][/ROW]
[ROW][C]9-4[/C][C]0.203[/C][C]-0.844[/C][C]1.251[/C][C]0.999[/C][/ROW]
[ROW][C]6-5[/C][C]-0.01[/C][C]-0.963[/C][C]0.944[/C][C]1[/C][/ROW]
[ROW][C]7-5[/C][C]0.179[/C][C]-0.704[/C][C]1.062[/C][C]0.999[/C][/ROW]
[ROW][C]8-5[/C][C]0.061[/C][C]-0.792[/C][C]0.913[/C][C]1[/C][/ROW]
[ROW][C]9-5[/C][C]-0.212[/C][C]-1.088[/C][C]0.664[/C][C]0.995[/C][/ROW]
[ROW][C]7-6[/C][C]0.188[/C][C]-0.545[/C][C]0.922[/C][C]0.993[/C][/ROW]
[ROW][C]8-6[/C][C]0.07[/C][C]-0.626[/C][C]0.766[/C][C]1[/C][/ROW]
[ROW][C]9-6[/C][C]-0.203[/C][C]-0.927[/C][C]0.522[/C][C]0.989[/C][/ROW]
[ROW][C]8-7[/C][C]-0.118[/C][C]-0.714[/C][C]0.478[/C][C]0.999[/C][/ROW]
[ROW][C]9-7[/C][C]-0.391[/C][C]-1.02[/C][C]0.238[/C][C]0.546[/C][/ROW]
[ROW][C]9-8[/C][C]-0.273[/C][C]-0.858[/C][C]0.313[/C][C]0.841[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147783&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147783&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
3-10-0.1-1.4781.2781
4-10-0.243-1.4830.9970.999
5-100.173-0.9271.2721
6-100.163-0.821.1461
7-100.352-0.5641.2670.936
8-100.233-0.6521.1190.992
9-10-0.039-0.9480.8691
4-3-0.143-1.6161.3311
5-30.273-1.0851.630.999
6-30.263-1.0021.5280.998
7-30.452-0.7611.6640.946
8-30.333-0.8571.5240.989
9-30.061-1.1471.2681
5-40.416-0.8011.6320.966
6-40.406-0.7071.5190.951
7-40.594-0.4591.6480.664
8-40.476-0.5511.5040.844
9-40.203-0.8441.2510.999
6-5-0.01-0.9630.9441
7-50.179-0.7041.0620.999
8-50.061-0.7920.9131
9-5-0.212-1.0880.6640.995
7-60.188-0.5450.9220.993
8-60.07-0.6260.7661
9-6-0.203-0.9270.5220.989
8-7-0.118-0.7140.4780.999
9-7-0.391-1.020.2380.546
9-8-0.273-0.8580.3130.841






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group70.7020.67
150 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 7 & 0.702 & 0.67 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147783&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]0.702[/C][C]0.67[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147783&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147783&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)
Group70.7020.67
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')