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Author*The author of this computation has been verified*
R Software Modulerwasp_twosampletests_mean.wasp
Title produced by softwarePaired and Unpaired Two Samples Tests about the Mean
Date of computationTue, 16 Dec 2014 14:22:43 +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/16/t14187397899owxnp53rqg6046.htm/, Retrieved Fri, 17 May 2024 00:05:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269611, Retrieved Fri, 17 May 2024 00:05:50 +0000
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Estimated Impact61
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-     [Paired and Unpaired Two Samples Tests about the Mean] [BS] [2014-12-11 09:49:38] [2568c9326b0361ae14a2b722dbd6de4e]
- R  D    [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-16 14:22:43] [72ee53c6f28232e74174360ca89644de] [Current]
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Dataseries X:
12.9	12.2
12.8	7.4
14.8	6.7
12	12.6
6.3	13.3
11.3	11.1
9.3	8.2
10	11.4
10.8	6.4
13.4	10.6
11.5	11.9
8.3	9.6
11.7	6.4
10.4	13.8
11.8	13.8
11.3	11.7
12.7	10.9
5.7	16.1
8	9.9
12.5	9
7.6	9.7
9.2	10.8
11.1	10.3
12.2	12.7
12.3	9.3
11.4	5.9
8.8	11.4
12.6	13
13	10.8
13.2	12.3
9.9	11.8
10.5	7.9
13.4	12.3
10.9	11.6
10.3	6.7
11.4	10.9
8.6	12.1
13.2	13.3
8.8	10.1
9	14.3
10.3	13.3
8.5	9.3
13.5	15.9
4.9	9.1
6.4	13
9.6	14.5
11.6	14.6
16.6	NA
19.1	12.6
13.35	7.7
18.4	4.3
16.15	11.8
18.4	11.2
16.35	12.6
17.65	5.6
14.35	9.9
14.75	7.7
9.9	7.3
16.85	11.4
15.6	13.6
14.85	7.9
11.75	10.7
18.45	8.3
17.1	9.6
19.9	14.2
18.45	11.1
15	4.35
11.35	12.7
18.1	18.1
19.1	17.85
7.6	12.6
13.4	17.1
13.9	16.1
15.25	14.7
16.1	10.6
17.35	12.6
13.15	16.2
12.15	13.6
18.2	18.9
13.6	14.1
14.75	14.5
14.1	14.75
14.9	14.8
16.25	12.45
13.6	12.65
15.65	17.35
14.6	8.6
19.2	16.1
11.9	11.6
13.2	17.75
16.35	15.25
15.65	17.65
17.75	13.6
7.65	18.25
19.3	16
15.2	18.25
17.1	14.6
19.05	13.85
18.55	18.95
19.1	15.9
11.85	16.1
13.35	10.95
11.4	15.1
19.9	15.95
17.6	14.6
16.1	15.4
11.95	15.4
15.15	17.6
16.85	13.35
7.7	15.35
12.6	19.1
12.35	12.9
16.65	12.6
13.95	10.35
15.7	15.4
15.35	9.6
15.1	14.85
17.75	19.25
14.6	13.6
16.65	12.75
NA	9.85
NA	12.65
NA	16.6
NA	11.2
NA	15.25
NA	12.4
NA	15.85
NA	18.15
NA	11.15
NA	12.35
NA	15.6
NA	15.6
NA	18.4
NA	13.1
NA	12.85
NA	9.5
NA	4.5
NA	13.6
NA	11.7
NA	12.4
NA	14.9
NA	11.2
NA	14.6
NA	14.05
NA	13.35
NA	11.85
NA	14.75
NA	13.2
NA	7.85
NA	7.85
NA	10.95
NA	9.95
NA	14.9
NA	13.4
NA	16.85
NA	10.95
NA	12.2
NA	15.2
NA	8.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269611&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269611&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269611&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 time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Two Sample t-test (unpaired)
Mean of Sample 113.4858333333333
Mean of Sample 212.5870253164557
t-stat2.2019226170436
df276
p-value0.0284980448892665
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.0952420048004201,1.70237402895486]
F-test to compare two variances
F-stat1.13841042854371
df119
p-value0.445657941330131
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.81487937220648,1.60313203783952]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 13.4858333333333 \tabularnewline
Mean of Sample 2 & 12.5870253164557 \tabularnewline
t-stat & 2.2019226170436 \tabularnewline
df & 276 \tabularnewline
p-value & 0.0284980448892665 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.0952420048004201,1.70237402895486] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.13841042854371 \tabularnewline
df & 119 \tabularnewline
p-value & 0.445657941330131 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.81487937220648,1.60313203783952] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269611&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]13.4858333333333[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.5870253164557[/C][/ROW]
[ROW][C]t-stat[/C][C]2.2019226170436[/C][/ROW]
[ROW][C]df[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]0.0284980448892665[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][0.0952420048004201,1.70237402895486][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.13841042854371[/C][/ROW]
[ROW][C]df[/C][C]119[/C][/ROW]
[ROW][C]p-value[/C][C]0.445657941330131[/C][/ROW]
[ROW][C]H0 value[/C][C]1[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][0.81487937220648,1.60313203783952][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269611&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269611&T=1

As an alternative you can also use a QR Code:  

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

Two Sample t-test (unpaired)
Mean of Sample 113.4858333333333
Mean of Sample 212.5870253164557
t-stat2.2019226170436
df276
p-value0.0284980448892665
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.0952420048004201,1.70237402895486]
F-test to compare two variances
F-stat1.13841042854371
df119
p-value0.445657941330131
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.81487937220648,1.60313203783952]







Welch Two Sample t-test (unpaired)
Mean of Sample 113.4858333333333
Mean of Sample 212.5870253164557
t-stat2.18245612091188
df247.313795114362
p-value0.0300170663589608
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.0876602205277192,1.70995581322756]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 13.4858333333333 \tabularnewline
Mean of Sample 2 & 12.5870253164557 \tabularnewline
t-stat & 2.18245612091188 \tabularnewline
df & 247.313795114362 \tabularnewline
p-value & 0.0300170663589608 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.0876602205277192,1.70995581322756] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269611&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]13.4858333333333[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.5870253164557[/C][/ROW]
[ROW][C]t-stat[/C][C]2.18245612091188[/C][/ROW]
[ROW][C]df[/C][C]247.313795114362[/C][/ROW]
[ROW][C]p-value[/C][C]0.0300170663589608[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]CI Level[/C][C]0.95[/C][/ROW]
[ROW][C]CI[/C][C][0.0876602205277192,1.70995581322756][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269611&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269611&T=2

As an alternative you can also use a QR Code:  

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

Welch Two Sample t-test (unpaired)
Mean of Sample 113.4858333333333
Mean of Sample 212.5870253164557
t-stat2.18245612091188
df247.313795114362
p-value0.0300170663589608
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.0876602205277192,1.70995581322756]







Wicoxon rank sum test with continuity correction (unpaired)
W10866.5
p-value0.0368284432353031
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.144409282700422
p-value0.116297842822261
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0757383966244726
p-value0.828857745675725

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 10866.5 \tabularnewline
p-value & 0.0368284432353031 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.144409282700422 \tabularnewline
p-value & 0.116297842822261 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0757383966244726 \tabularnewline
p-value & 0.828857745675725 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269611&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]10866.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.0368284432353031[/C][/ROW]
[ROW][C]H0 value[/C][C]0[/C][/ROW]
[ROW][C]Alternative[/C][C]two.sided[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributions of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.144409282700422[/C][/ROW]
[ROW][C]p-value[/C][C]0.116297842822261[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0757383966244726[/C][/ROW]
[ROW][C]p-value[/C][C]0.828857745675725[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269611&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269611&T=3

As an alternative you can also use a QR Code:  

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

Wicoxon rank sum test with continuity correction (unpaired)
W10866.5
p-value0.0368284432353031
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.144409282700422
p-value0.116297842822261
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0757383966244726
p-value0.828857745675725



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 0.0 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 0.0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1) #column number of first sample
par2 <- as.numeric(par2) #column number of second sample
par3 <- as.numeric(par3) #confidence (= 1 - alpha)
if (par5 == 'unpaired') paired <- FALSE else paired <- TRUE
par6 <- as.numeric(par6) #H0
z <- t(y)
if (par1 == par2) stop('Please, select two different column numbers')
if (par1 < 1) stop('Please, select a column number greater than zero for the first sample')
if (par2 < 1) stop('Please, select a column number greater than zero for the second sample')
if (par1 > length(z[1,])) stop('The column number for the first sample should be smaller')
if (par2 > length(z[1,])) stop('The column number for the second sample should be smaller')
if (par3 <= 0) stop('The confidence level should be larger than zero')
if (par3 >= 1) stop('The confidence level should be smaller than zero')
(r.t <- t.test(z[,par1],z[,par2],var.equal=TRUE,alternative=par4,paired=paired,mu=par6,conf.level=par3))
(v.t <- var.test(z[,par1],z[,par2],conf.level=par3))
(r.w <- t.test(z[,par1],z[,par2],var.equal=FALSE,alternative=par4,paired=paired,mu=par6,conf.level=par3))
(w.t <- wilcox.test(z[,par1],z[,par2],alternative=par4,paired=paired,mu=par6,conf.level=par3))
(ks.t <- ks.test(z[,par1],z[,par2],alternative=par4))
m1 <- mean(z[,par1],na.rm=T)
m2 <- mean(z[,par2],na.rm=T)
mdiff <- m1 - m2
newsam1 <- z[!is.na(z[,par1]),par1]
newsam2 <- z[,par2]+mdiff
newsam2 <- newsam2[!is.na(newsam2)]
(ks1.t <- ks.test(newsam1,newsam2,alternative=par4))
mydf <- data.frame(cbind(z[,par1],z[,par2]))
colnames(mydf) <- c('Variable 1','Variable 2')
bitmap(file='test1.png')
boxplot(mydf, notch=TRUE, ylab='value',main=main)
dev.off()
bitmap(file='test2.png')
qqnorm(z[,par1],main='Normal QQplot - Variable 1')
qqline(z[,par1])
dev.off()
bitmap(file='test3.png')
qqnorm(z[,par2],main='Normal QQplot - Variable 2')
qqline(z[,par2])
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Two Sample t-test (',par5,')',sep=''),2,TRUE)
a<-table.row.end(a)
if(!paired){
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 1',header=TRUE)
a<-table.element(a,r.t$estimate[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 2',header=TRUE)
a<-table.element(a,r.t$estimate[[2]])
a<-table.row.end(a)
} else {
a<-table.row.start(a)
a<-table.element(a,'Difference: Mean1 - Mean2',header=TRUE)
a<-table.element(a,r.t$estimate)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'t-stat',header=TRUE)
a<-table.element(a,r.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'df',header=TRUE)
a<-table.element(a,r.t$parameter[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,r.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,r.t$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,r.t$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI Level',header=TRUE)
a<-table.element(a,attr(r.t$conf.int,'conf.level'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI',header=TRUE)
a<-table.element(a,paste('[',r.t$conf.int[1],',',r.t$conf.int[2],']',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'F-test to compare two variances',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'F-stat',header=TRUE)
a<-table.element(a,v.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'df',header=TRUE)
a<-table.element(a,v.t$parameter[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,v.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,v.t$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,v.t$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI Level',header=TRUE)
a<-table.element(a,attr(v.t$conf.int,'conf.level'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI',header=TRUE)
a<-table.element(a,paste('[',v.t$conf.int[1],',',v.t$conf.int[2],']',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Welch Two Sample t-test (',par5,')',sep=''),2,TRUE)
a<-table.row.end(a)
if(!paired){
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 1',header=TRUE)
a<-table.element(a,r.w$estimate[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Mean of Sample 2',header=TRUE)
a<-table.element(a,r.w$estimate[[2]])
a<-table.row.end(a)
} else {
a<-table.row.start(a)
a<-table.element(a,'Difference: Mean1 - Mean2',header=TRUE)
a<-table.element(a,r.w$estimate)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'t-stat',header=TRUE)
a<-table.element(a,r.w$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'df',header=TRUE)
a<-table.element(a,r.w$parameter[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,r.w$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,r.w$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,r.w$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI Level',header=TRUE)
a<-table.element(a,attr(r.w$conf.int,'conf.level'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'CI',header=TRUE)
a<-table.element(a,paste('[',r.w$conf.int[1],',',r.w$conf.int[2],']',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Wicoxon rank sum test with continuity correction (',par5,')',sep=''),2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'W',header=TRUE)
a<-table.element(a,w.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,w.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'H0 value',header=TRUE)
a<-table.element(a,w.t$null.value[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Alternative',header=TRUE)
a<-table.element(a,w.t$alternative)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Kolmogorov-Smirnov Test to compare Distributions of two Samples',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'KS Statistic',header=TRUE)
a<-table.element(a,ks.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,ks.t$p.value)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'KS Statistic',header=TRUE)
a<-table.element(a,ks1.t$statistic[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,ks1.t$p.value)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')