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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 17:51:51 +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/t1418233981x2r9krtw0bpvj59.htm/, Retrieved Sat, 18 May 2024 14:41:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265539, Retrieved Sat, 18 May 2024 14:41:41 +0000
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Estimated Impact47

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12 12.9
8 12.2
11 12.8
13 7.4
11 6.7
10 12.6
7 14.8
10 13.3
15 11.1
12 8.2
12 11.4
10 6.4
10 10.6
14 12
6 6.3
12 11.3
14 11.9
11 9.3
8 9.6
12 10
15 6.4
13 13.8
11 10.8
12 13.8
7 11.7
11 10.9
7 16.1
12 13.4
12 9.9
13 11.5
9 8.3
11 11.7
12 9
15 9.7
12 10.8
6 10.3
5 10.4
13 12.7
11 9.3
6 11.8
12 5.9
10 11.4
6 13
12 10.8
11 12.3
6 11.3
12 11.8
12 7.9
8 12.7
10 12.3
11 11.6
7 6.7
12 10.9
13 12.1
14 13.3
12 10.1
6 5.7
14 14.3
10 8
12 13.3
11 9.3
10 12.5
7 7.6
12 15.9
7 9.2
12 9.1
12 11.1
10 13
10 14.5
12 12.2
12 12.3
12 11.4
8 8.8
10 14.6
5 12.6
10 13
12 12.6
11 13.2
9 9.9
12 7.7
11 10.5
10 13.4
12 10.9
10 4.3
9 10.3
11 11.8
12 11.2
7 11.4
11 8.6
12 13.2
6 12.6
9 5.6
15 9.9
10 8.8
11 7.7
12 9
12 7.3
12 11.4
11 13.6
9 7.9
11 10.7
12 10.3
12 8.3
14 9.6
8 14.2
10 8.5
9 13.5
10 4.9
9 6.4
10 9.6
12 11.6
11 11.1
9 4.35
11 12.7
12 18.1
12 17.85
7 16.6
12 12.6
12 17.1
12 19.1
10 16.1
15 13.35
10 18.4
15 14.7
10 10.6
15 12.6
9 16.2
15 13.6
12 18.9
13 14.1
12 14.5
12 16.15
8 14.75
9 14.8
15 12.45
12 12.65
12 17.35
15 8.6
11 18.4
12 16.1
6 11.6
14 17.75
12 15.25
12 17.65
12 16.35
11 17.65
12 13.6
12 14.35
12 14.75
12 18.25
8 9.9
8 16
12 18.25
12 16.85
11 14.6
10 13.85
11 18.95
12 15.6
13 14.85
12 11.75
12 18.45
10 15.9
10 17.1
11 16.1
8 19.9
12 10.95
9 18.45
12 15.1
9 15
11 11.35
15 15.95
8 18.1
8 14.6
11 15.4
11 15.4
11 17.6
13 13.35
7 19.1
12 15.35
8 7.6
8 13.4
4 13.9
11 19.1
10 15.25
7 12.9
12 16.1
11 17.35
9 13.15
10 12.15
8 12.6
8 10.35
11 15.4
12 9.6
10 18.2
10 13.6
12 14.85
8 14.75
11 14.1
8 14.9
10 16.25
14 19.25
9 13.6
9 13.6
10 15.65
13 12.75
12 14.6
13 9.85
8 12.65
3 19.2
8 16.6
12 11.2
11 15.25
9 11.9
12 13.2
12 16.35
12 12.4
10 15.85
13 18.15
9 11.15
12 15.65
11 17.75
14 7.65
11 12.35
9 15.6
12 19.3
8 15.2
15 17.1
12 15.6
14 18.4
12 19.05
9 18.55
9 19.1
13 13.1
13 12.85
15 9.5
11 4.5
7 11.85
10 13.6
11 11.7
14 12.4
14 13.35
13 11.4
12 14.9
8 19.9
13 11.2
9 14.6
12 17.6
13 14.05
11 16.1
11 13.35
13 11.85
12 11.95
12 14.75
10 15.15
9 13.2
10 16.85
13 7.85
13 7.7
9 12.6
11 7.85
12 10.95
8 12.35
12 9.95
12 14.9
12 16.65
9 13.4
12 13.95
12 15.7
11 16.85
12 10.95
6 15.35
7 12.2
10 15.1
12 17.75
10 15.2
12 14.6
9 16.65
3 8.1

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=265539&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=265539&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265539&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 110.7410071942446
Mean of Sample 212.975
t-stat-9.10007546080053
df554
p-value1.6183863445893e-18
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.7162011313414,-1.75178448016939]
F-test to compare two variances
F-stat0.454128408273251
df277
p-value9.12825768414072e-11
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.358657864731512,0.575012097825264]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 10.7410071942446 \tabularnewline
Mean of Sample 2 & 12.975 \tabularnewline
t-stat & -9.10007546080053 \tabularnewline
df & 554 \tabularnewline
p-value & 1.6183863445893e-18 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-2.7162011313414,-1.75178448016939] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.454128408273251 \tabularnewline
df & 277 \tabularnewline
p-value & 9.12825768414072e-11 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.358657864731512,0.575012097825264] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265539&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]10.7410071942446[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.975[/C][/ROW]
[ROW][C]t-stat[/C][C]-9.10007546080053[/C][/ROW]
[ROW][C]df[/C][C]554[/C][/ROW]
[ROW][C]p-value[/C][C]1.6183863445893e-18[/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][-2.7162011313414,-1.75178448016939][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.454128408273251[/C][/ROW]
[ROW][C]df[/C][C]277[/C][/ROW]
[ROW][C]p-value[/C][C]9.12825768414072e-11[/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][0.358657864731512,0.575012097825264][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265539&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265539&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 110.7410071942446
Mean of Sample 212.975
t-stat-9.10007546080053
df554
p-value1.6183863445893e-18
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.7162011313414,-1.75178448016939]
F-test to compare two variances
F-stat0.454128408273251
df277
p-value9.12825768414072e-11
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.358657864731512,0.575012097825264]






Welch Two Sample t-test (unpaired)
Mean of Sample 110.7410071942446
Mean of Sample 212.975
t-stat-9.10007546080053
df485.572654931728
p-value2.33456086381343e-18
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.71634995237773,-1.75163565913306]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 10.7410071942446 \tabularnewline
Mean of Sample 2 & 12.975 \tabularnewline
t-stat & -9.10007546080053 \tabularnewline
df & 485.572654931728 \tabularnewline
p-value & 2.33456086381343e-18 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-2.71634995237773,-1.75163565913306] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265539&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]10.7410071942446[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]12.975[/C][/ROW]
[ROW][C]t-stat[/C][C]-9.10007546080053[/C][/ROW]
[ROW][C]df[/C][C]485.572654931728[/C][/ROW]
[ROW][C]p-value[/C][C]2.33456086381343e-18[/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][-2.71634995237773,-1.75163565913306][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265539&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265539&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 110.7410071942446
Mean of Sample 212.975
t-stat-9.10007546080053
df485.572654931728
p-value2.33456086381343e-18
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-2.71634995237773,-1.75163565913306]






Wicoxon rank sum test with continuity correction (unpaired)
W22878.5
p-value7.2938361449253e-17
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.460431654676259
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.212230215827338
p-value7.29416712441644e-06

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 22878.5 \tabularnewline
p-value & 7.2938361449253e-17 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.460431654676259 \tabularnewline
p-value & 0 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.212230215827338 \tabularnewline
p-value & 7.29416712441644e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265539&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]22878.5[/C][/ROW]
[ROW][C]p-value[/C][C]7.2938361449253e-17[/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]0.460431654676259[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.212230215827338[/C][/ROW]
[ROW][C]p-value[/C][C]7.29416712441644e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265539&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265539&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)
W22878.5
p-value7.2938361449253e-17
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.460431654676259
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.212230215827338
p-value7.29416712441644e-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 = 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')