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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 computationSat, 06 Dec 2014 16:26:15 +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/06/t14178832449tr96tfunz4t0vs.htm/, Retrieved Sun, 19 May 2024 13:55:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263651, Retrieved Sun, 19 May 2024 13:55:44 +0000
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User-defined keywords
Estimated Impact74

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-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-18 15:27:39] [8f0f7d8870e334acea674e48ede2c797]
- R PD    [Paired and Unpaired Two Samples Tests about the Mean] [paper] [2014-12-06 16:26:15] [984e7ebcf70ed344d92ecabf69fab39c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12,9	11,3
7,4	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
6,1	13,2
9	12,6
9,7	5,6
10,8	9,9
10,3	8,8
10,4	7,7
9,3	9
11,8	7,3
5,9	11,4
11,4	13,6
13	7,9
10,8	10,7
11,3	10,3
11,8	8,3
12,7	9,6
10,9	14,2
13,3	8,5
10,1	13,5
14,3	4,9
9,3	6,4
12,5	9,6
7,6	11,6
15,9	11,1
9,2	16,6
11,1	12,6
13	18,6
14,5	11,6
12,3	14,6
11,4	13,85
7,3	14,85
12,6	11,75
13	18,45
13,2	15,9
7,7	19,9
4,35	10,95
12,7	18,45
18,1	15,1
17,85	15
17,1	11,35
19,1	15,95
16,1	18,1
13,35	14,6
18,4	17,6
14,7	15,35
10,6	13,4
12,6	13,9
16,2	15,25
13,6	12,9
14,1	16,1
14,5	17,35
16,15	13,15
14,75	12,15
14,8	12,6
12,45	10,35
12,65	15,4
17,35	9,6
8,6	18,2
18,4	13,6
16,1	14,85
17,75	14,1
15,25	14,9
17,65	16,25
15,6	13,6
16,35	15,65
17,65	14,6
13,6	12,65
11,7	11,9
14,35	19,2
14,75	11,2
18,25	13,2
9,9	15,85
16	11,15
18,25	15,65
16,85	7,65
18,95	15,2
15,6	15,6
17,1	13,1
16,1	11,85
15,4	12,4
15,4	11,4
13,35	19,9
19,1	14,9
7,6	11,2
19,1	14,6
14,75	14,75
19,25	15,15
13,6	16,85
12,75	7,85
9,85	12,6
15,25	7,85
11,9	10,95
16,35	12,35
12,4	9,95
14,35	14,9
18,15	16,65
17,75	13,4
12,35	13,95
15,6	15,7
19,3	16,85
17,1	10,95
18,4	15,35
19,05	12,2
18,55	15,1
19,1	17,75
12,85	15,2
9,5	16,65
4,5	8,1
13,6	NA
11,7	NA
13,35	NA
17,75	NA
17,6	NA
14,05	NA
16,1	NA
13,35	NA
11,85	NA
11,95	NA
13,2	NA
7,7	NA
14,6	NA

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'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263651&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263651&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'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Two Sample t-test (unpaired)
Mean of Sample 113.1224832214765
Mean of Sample 212.6985294117647
t-stat1.04589689974591
df283
p-value0.296501131739986
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.373928864584015,1.22183648400762]
F-test to compare two variances
F-stat1.17349753765441
df148
p-value0.344843866651436
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.841552643399328,1.63220608455181]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 13.1224832214765 \tabularnewline
Mean of Sample 2 & 12.6985294117647 \tabularnewline
t-stat & 1.04589689974591 \tabularnewline
df & 283 \tabularnewline
p-value & 0.296501131739986 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.373928864584015,1.22183648400762] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.17349753765441 \tabularnewline
df & 148 \tabularnewline
p-value & 0.344843866651436 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.841552643399328,1.63220608455181] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263651&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]13.1224832214765[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.6985294117647[/C][/ROW]
[ROW][C]t-stat[/C][C]1.04589689974591[/C][/ROW]
[ROW][C]df[/C][C]283[/C][/ROW]
[ROW][C]p-value[/C][C]0.296501131739986[/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][-0.373928864584015,1.22183648400762][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.17349753765441[/C][/ROW]
[ROW][C]df[/C][C]148[/C][/ROW]
[ROW][C]p-value[/C][C]0.344843866651436[/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][0.841552643399328,1.63220608455181][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263651&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 113.1224832214765
Mean of Sample 212.6985294117647
t-stat1.04589689974591
df283
p-value0.296501131739986
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.373928864584015,1.22183648400762]
F-test to compare two variances
F-stat1.17349753765441
df148
p-value0.344843866651436
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.841552643399328,1.63220608455181]






Welch Two Sample t-test (unpaired)
Mean of Sample 113.1224832214765
Mean of Sample 212.6985294117647
t-stat1.04972553032997
df282.961835660719
p-value0.294740036523276
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.371019232922978,1.21892685234659]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 13.1224832214765 \tabularnewline
Mean of Sample 2 & 12.6985294117647 \tabularnewline
t-stat & 1.04972553032997 \tabularnewline
df & 282.961835660719 \tabularnewline
p-value & 0.294740036523276 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.371019232922978,1.21892685234659] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263651&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]13.1224832214765[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.6985294117647[/C][/ROW]
[ROW][C]t-stat[/C][C]1.04972553032997[/C][/ROW]
[ROW][C]df[/C][C]282.961835660719[/C][/ROW]
[ROW][C]p-value[/C][C]0.294740036523276[/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][-0.371019232922978,1.21892685234659][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263651&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263651&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 113.1224832214765
Mean of Sample 212.6985294117647
t-stat1.04972553032997
df282.961835660719
p-value0.294740036523276
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.371019232922978,1.21892685234659]






Wicoxon rank sum test with continuity correction (unpaired)
W10823
p-value0.320391126906979
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.108616265298066
p-value0.371196361288346
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0856198183971575
p-value0.674432031607528

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 10823 \tabularnewline
p-value & 0.320391126906979 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.108616265298066 \tabularnewline
p-value & 0.371196361288346 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0856198183971575 \tabularnewline
p-value & 0.674432031607528 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263651&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]10823[/C][/ROW]
[ROW][C]p-value[/C][C]0.320391126906979[/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]0.108616265298066[/C][/ROW]
[ROW][C]p-value[/C][C]0.371196361288346[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0856198183971575[/C][/ROW]
[ROW][C]p-value[/C][C]0.674432031607528[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263651&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263651&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)
W10823
p-value0.320391126906979
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.108616265298066
p-value0.371196361288346
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0856198183971575
p-value0.674432031607528


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 = unpaired ; par6 = 0.0 ;
R code (references can be found in the software module):
par6 <- '0.0'
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')