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Description of Statistical Computation

Author's title

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 computationWed, 10 Dec 2014 18:07:25 +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/10/t1418234926xfpdq2mp06yvafr.htm/, Retrieved Sun, 19 May 2024 14:12:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265557, Retrieved Sun, 19 May 2024 14:12:41 +0000
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Estimated Impact67

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 13
12.2 8
12.8 14
7.4 16
6.7 14
12.6 13
14.8 15
13.3 13
11.1 20
8.2 17
11.4 15
6.4 16
10.6 12
12 17
6.3 11
11.3 16
11.9 16
9.3 15
9.6 13
10 14
6.4 19
13.8 16
10.8 17
13.8 10
11.7 15
10.9 14
16.1 14
13.4 16
9.9 15
11.5 17
8.3 14
11.7 16
9 15
9.7 16
10.8 16
10.3 10
10.4 8
12.7 17
9.3 14
11.8 10
5.9 14
11.4 12
13 16
10.8 16
12.3 16
11.3 8
11.8 16
7.9 15
12.7 8
12.3 13
11.6 14
6.7 13
10.9 16
12.1 19
13.3 19
10.1 14
5.7 15
14.3 13
8 10
13.3 16
9.3 15
12.5 11
7.6 9
15.9 16
9.2 12
9.1 12
11.1 14
13 14
14.5 13
12.2 15
12.3 17
11.4 14
8.8 11
14.6 9
12.6 7
13 15
12.6 12
13.2 15
9.9 14
7.7 16
10.5 14
13.4 13
10.9 16
4.3 13
10.3 16
11.8 16
11.2 16
11.4 10
8.6 12
13.2 12
12.6 12
5.6 12
9.9 19
8.8 14
7.7 13
9 16
7.3 15
11.4 12
13.6 8
7.9 10
10.7 16
10.3 16
8.3 10
9.6 18
14.2 12
8.5 16
13.5 10
4.9 14
6.4 12
9.6 11
11.6 15
11.1 7
4.35 16
12.7 16
18.1 16
17.85 16
16.6 12
12.6 15
17.1 14
19.1 15
16.1 16
13.35 13
18.4 10
14.7 17
10.6 15
12.6 18
16.2 16
13.6 20
18.9 16
14.1 17
14.5 16
16.15 15
14.75 13
14.8 16
12.45 16
12.65 16
17.35 17
8.6 20
18.4 14
16.1 17
11.6 6
17.75 16
15.25 15
17.65 16
16.35 16
17.65 14
13.6 16
14.35 16
14.75 16
18.25 14
9.9 14
16 16
18.25 16
16.85 15
14.6 16
13.85 16
18.95 18
15.6 15
14.85 16
11.75 16
18.45 16
15.9 17
17.1 14
16.1 18
19.9 9
10.95 15
18.45 14
15.1 15
15 13
11.35 16
15.95 20
18.1 14
14.6 12
15.4 15
15.4 15
17.6 15
13.35 16
19.1 11
15.35 16
7.6 7
13.4 11
13.9 9
19.1 15
15.25 16
12.9 14
16.1 15
17.35 13
13.15 13
12.15 12
12.6 16
10.35 14
15.4 16
9.6 14
18.2 15
13.6 10
14.85 16
14.75 14
14.1 16
14.9 12
16.25 16
19.25 16
13.6 15
13.6 14
15.65 16
12.75 11
14.6 15
9.85 18
12.65 13
19.2 7
16.6 7
11.2 17
15.25 18
11.9 15
13.2 8
16.35 13
12.4 13
15.85 15
18.15 18
11.15 16
15.65 14
17.75 15
7.65 19
12.35 16
15.6 12
19.3 16
15.2 11
17.1 16
15.6 15
18.4 19
19.05 15
18.55 14
19.1 14
13.1 17
12.85 16
9.5 20
4.5 16
11.85 9
13.6 13
11.7 15
12.4 19
13.35 16
11.4 17
14.9 16
19.9 9
11.2 11
14.6 14
17.6 19
14.05 13
16.1 14
13.35 15
11.85 15
11.95 14
14.75 16
15.15 17
13.2 12
16.85 15
7.85 17
7.7 15
12.6 10
7.85 16
10.95 15
12.35 11
9.95 16
14.9 16
16.65 16
13.4 14
13.95 14
15.7 16
16.85 16
10.95 18
15.35 14
12.2 20
15.1 15
17.75 16
15.2 16
14.6 16
16.65 12
8.1 8

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=265557&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=265557&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265557&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






Two Sample t-test (paired)
Difference: Mean1 - Mean2-1.40989208633094
t-stat-5.5678446789193
df277
p-value6.09466840097209e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.90837299598792,-0.911411176673953]
F-test to compare two variances
F-stat1.53746907691695
df277
p-value0.000367202194597738
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.21424990415038,1.9467254264515]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -1.40989208633094 \tabularnewline
t-stat & -5.5678446789193 \tabularnewline
df & 277 \tabularnewline
p-value & 6.09466840097209e-08 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-1.90837299598792,-0.911411176673953] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.53746907691695 \tabularnewline
df & 277 \tabularnewline
p-value & 0.000367202194597738 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.21424990415038,1.9467254264515] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265557&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-1.40989208633094[/C][/ROW]
[ROW][C]t-stat[/C][C]-5.5678446789193[/C][/ROW]
[ROW][C]df[/C][C]277[/C][/ROW]
[ROW][C]p-value[/C][C]6.09466840097209e-08[/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][-1.90837299598792,-0.911411176673953][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.53746907691695[/C][/ROW]
[ROW][C]df[/C][C]277[/C][/ROW]
[ROW][C]p-value[/C][C]0.000367202194597738[/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][1.21424990415038,1.9467254264515][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265557&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265557&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:

Two Sample t-test (paired)
Difference: Mean1 - Mean2-1.40989208633094
t-stat-5.5678446789193
df277
p-value6.09466840097209e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.90837299598792,-0.911411176673953]
F-test to compare two variances
F-stat1.53746907691695
df277
p-value0.000367202194597738
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.21424990415038,1.9467254264515]






Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-1.40989208633094
t-stat-5.5678446789193
df277
p-value6.09466840097209e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.90837299598792,-0.911411176673953]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -1.40989208633094 \tabularnewline
t-stat & -5.5678446789193 \tabularnewline
df & 277 \tabularnewline
p-value & 6.09466840097209e-08 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-1.90837299598792,-0.911411176673953] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265557&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-1.40989208633094[/C][/ROW]
[ROW][C]t-stat[/C][C]-5.5678446789193[/C][/ROW]
[ROW][C]df[/C][C]277[/C][/ROW]
[ROW][C]p-value[/C][C]6.09466840097209e-08[/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][-1.90837299598792,-0.911411176673953][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265557&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265557&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:

Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-1.40989208633094
t-stat-5.5678446789193
df277
p-value6.09466840097209e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.90837299598792,-0.911411176673953]






Wicoxon rank sum test with continuity correction (paired)
W12223
p-value1.3889285284896e-07
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.330935251798561
p-value1.19793064357054e-13
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.215827338129496
p-value4.75414776524019e-06

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 12223 \tabularnewline
p-value & 1.3889285284896e-07 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.330935251798561 \tabularnewline
p-value & 1.19793064357054e-13 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.215827338129496 \tabularnewline
p-value & 4.75414776524019e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265557&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]12223[/C][/ROW]
[ROW][C]p-value[/C][C]1.3889285284896e-07[/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]0.330935251798561[/C][/ROW]
[ROW][C]p-value[/C][C]1.19793064357054e-13[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.215827338129496[/C][/ROW]
[ROW][C]p-value[/C][C]4.75414776524019e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265557&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265557&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:

Wicoxon rank sum test with continuity correction (paired)
W12223
p-value1.3889285284896e-07
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.330935251798561
p-value1.19793064357054e-13
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.215827338129496
p-value4.75414776524019e-06


Figures (Output of Computation)

Input Parameters & R Code

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 = paired ; 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')