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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 computationTue, 09 Dec 2014 19:19:05 +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/09/t1418152842y8xj4nscgv6tc2j.htm/, Retrieved Thu, 16 May 2024 08:18:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264825, Retrieved Thu, 16 May 2024 08:18:28 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-09 19:19:05] [18673d63f90870b9c004059cd6229007] [Current]
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Dataset

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

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'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=264825&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=264825&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264825&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'Sir Maurice George Kendall' @ kendall.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 112.7352941176471
Mean of Sample 213.2045774647887
t-stat-3.48706952408692
df276
p-value0.000568023392810669
H0 value0.95
Alternativetwo.sided
CI Level0.95
CI[-1.27052805690524,0.331961362621891]
F-test to compare two variances
F-stat0.893023115533932
df135
p-value0.508278403444606
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.639113073698362,1.24935138057088]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 12.7352941176471 \tabularnewline
Mean of Sample 2 & 13.2045774647887 \tabularnewline
t-stat & -3.48706952408692 \tabularnewline
df & 276 \tabularnewline
p-value & 0.000568023392810669 \tabularnewline
H0 value & 0.95 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-1.27052805690524,0.331961362621891] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.893023115533932 \tabularnewline
df & 135 \tabularnewline
p-value & 0.508278403444606 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.639113073698362,1.24935138057088] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264825&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]12.7352941176471[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.2045774647887[/C][/ROW]
[ROW][C]t-stat[/C][C]-3.48706952408692[/C][/ROW]
[ROW][C]df[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]0.000568023392810669[/C][/ROW]
[ROW][C]H0 value[/C][C]0.95[/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][-1.27052805690524,0.331961362621891][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.893023115533932[/C][/ROW]
[ROW][C]df[/C][C]135[/C][/ROW]
[ROW][C]p-value[/C][C]0.508278403444606[/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][0.639113073698362,1.24935138057088][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264825&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264825&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 (unpaired)
Mean of Sample 112.7352941176471
Mean of Sample 213.2045774647887
t-stat-3.48706952408692
df276
p-value0.000568023392810669
H0 value0.95
Alternativetwo.sided
CI Level0.95
CI[-1.27052805690524,0.331961362621891]
F-test to compare two variances
F-stat0.893023115533932
df135
p-value0.508278403444606
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.639113073698362,1.24935138057088]






Welch Two Sample t-test (unpaired)
Mean of Sample 112.7352941176471
Mean of Sample 213.2045774647887
t-stat-3.49134058638828
df275.951662490508
p-value0.000559414240875757
H0 value0.95
Alternativetwo.sided
CI Level0.95
CI[-1.26954848742017,0.330981793136817]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 12.7352941176471 \tabularnewline
Mean of Sample 2 & 13.2045774647887 \tabularnewline
t-stat & -3.49134058638828 \tabularnewline
df & 275.951662490508 \tabularnewline
p-value & 0.000559414240875757 \tabularnewline
H0 value & 0.95 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-1.26954848742017,0.330981793136817] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264825&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]12.7352941176471[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.2045774647887[/C][/ROW]
[ROW][C]t-stat[/C][C]-3.49134058638828[/C][/ROW]
[ROW][C]df[/C][C]275.951662490508[/C][/ROW]
[ROW][C]p-value[/C][C]0.000559414240875757[/C][/ROW]
[ROW][C]H0 value[/C][C]0.95[/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][-1.26954848742017,0.330981793136817][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264825&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264825&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 (unpaired)
Mean of Sample 112.7352941176471
Mean of Sample 213.2045774647887
t-stat-3.49134058638828
df275.951662490508
p-value0.000559414240875757
H0 value0.95
Alternativetwo.sided
CI Level0.95
CI[-1.26954848742017,0.330981793136817]






Wicoxon rank sum test with continuity correction (unpaired)
W7470
p-value0.00110754621144644
H0 value0.95
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.106462303231152
p-value0.410456647753738
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.081089478044739
p-value0.750956151320181

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 7470 \tabularnewline
p-value & 0.00110754621144644 \tabularnewline
H0 value & 0.95 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.106462303231152 \tabularnewline
p-value & 0.410456647753738 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.081089478044739 \tabularnewline
p-value & 0.750956151320181 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264825&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]7470[/C][/ROW]
[ROW][C]p-value[/C][C]0.00110754621144644[/C][/ROW]
[ROW][C]H0 value[/C][C]0.95[/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]0.106462303231152[/C][/ROW]
[ROW][C]p-value[/C][C]0.410456647753738[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.081089478044739[/C][/ROW]
[ROW][C]p-value[/C][C]0.750956151320181[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264825&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264825&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 (unpaired)
W7470
p-value0.00110754621144644
H0 value0.95
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.106462303231152
p-value0.410456647753738
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.081089478044739
p-value0.750956151320181


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 0.95 ;
R code (references can be found in the software module):
par6 <- ''
par5 <- 'unpaired'
par4 <- 'two.sided'
par3 <- '0.95'
par2 <- '2'
par1 <- '1'
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')