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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, 17 Dec 2013 05:28:43 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/17/t1387276151ijek54s23cgqwhr.htm/, Retrieved Fri, 29 Mar 2024 08:51:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232403, Retrieved Fri, 29 Mar 2024 08:51:12 +0000
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Original text written by user:
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Estimated Impact187
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-       [Paired and Unpaired Two Samples Tests about the Mean] [] [2013-12-17 10:28:43] [9e6a405f514733ea23d87e4507d39d29] [Current]
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Dataseries X:
15	NA
0	NA
3	NA
NA	2
NA	3
NA	12
NA	3
0	NA
12	NA
NA	NA
NA	0
10	NA
12	NA
20	NA
20	NA
NA	2
NA	3
16	NA
NA	4
2	NA
NA	4
16	NA
NA	0
NA	0
15	NA
NA	9
1	NA
15	NA
5	NA
NA	4
NA	15
NA	4
12	NA
NA	2
4	NA
2	NA
NA	4
8	NA
NA	30
6	NA
NA	6
7	NA
NA	4
17	NA
5	NA
NA	0
3	NA
4	NA
15	NA
NA	0
8	NA
NA	10
NA	4
0	NA
6	NA
11	NA
NA	10
0	NA
NA	0
NA	0
0	NA
0	NA
NA	0
0	NA
NA	7
NA	4
12	NA
6	NA
12	NA
10	NA
NA	9
6	NA
NA	0
16	NA
2	NA
0	NA
NA	0
NA	1
10	NA
10	NA
14	NA
12	NA
12	NA
12	NA
NA	5
0	NA
4	NA
3	NA
NA	0
14	NA
4	NA
NA	3
NA	0
NA	12
12	NA
15	NA
NA	0
8	NA
6	NA
14	NA
NA	5
10	NA
16	NA
4	NA
NA	0
NA	8
12	NA
6	NA
4	NA
20	NA
NA	0
13	NA
NA	0
0	NA
NA	0
0	NA
10	NA
6	NA
16	NA
6	NA
0	NA
0	NA
4	NA
9	NA
17	NA
NA	12
3	NA
NA	6
NA	8
NA	3
NA	7
NA	0
10	NA
3	NA
0	NA
NA	8
0	NA
4	NA
13	NA
NA	12
16	NA
20	NA
NA	20
NA	21
10	NA
14	NA
12	NA
NA	15
NA	9
NA	4
8	NA
0	NA
13	NA
0	NA
21	NA
NA	0
NA	1
16	NA
12	NA
2	NA
NA	0
NA	4
NA	6
10	NA
NA	3
NA	0
16	NA
NA	4
NA	0
NA	0
0	NA
NA	0
NA	3
4	NA
NA	15
25	NA
12	NA
4	NA
NA	0
NA	9
NA	5
15	NA
NA	0
10	NA
NA	3
12	NA
0	NA
12	NA
5	NA
15	NA
NA	1
2	NA
NA	4
NA	3
NA	8
NA	0
NA	0
0	NA
2	NA
NA	22
NA	0
26	NA
21	NA
NA	0
NA	0
NA	4
4	NA
NA	0
18	NA
NA	1
18	NA
6	NA
NA	6
0	NA
NA	8
3	NA
NA	7
15	NA
NA	0
NA	0
NA	2
NA	27
NA	3
8	NA
NA	4
NA	0
0	NA
NA	0
8	NA
NA	4
NA	3
NA	8
NA	0
NA	6
NA	4
5	NA
NA	0
NA	6
8	NA
NA	5
6	NA
NA	12
0	NA
8	NA
13	NA
NA	6
NA	11
12	NA
0	NA
NA	4
NA	5
0	NA
7	NA
NA	0
NA	0
NA	4
NA	8
NA	0
NA	0
NA	2
9	NA
NA	4
0	NA
NA	0
12	NA
0	NA
NA	1
NA	3
11	NA
0	NA
NA	12
1	NA
0	NA
NA	6
NA	0
3	NA
NA	9
12	NA
NA	5
0	NA
NA	0
15	NA
5	NA
0	NA
0	NA
0	NA
6	NA
NA	10
18	NA
NA	8
10	NA
4	NA
1	NA
13	NA
8	NA
0	NA
0	NA
NA	4
NA	12
4	NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 4 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232403&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232403&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232403&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 time4 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Two Sample t-test (unpaired)
Mean of Sample 17.82822085889571
Mean of Sample 24.625
t-stat4.58679712391375
df297
p-value6.64443222905169e-06
H0 value0
Alternativetwo.sided
CI Level0.95
CI[1.82886622577225,4.57757549201916]
F-test to compare two variances
F-stat1.34734248810557
df162
p-value0.0735165793361643
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.971846144948785,1.85890235586194]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 7.82822085889571 \tabularnewline
Mean of Sample 2 & 4.625 \tabularnewline
t-stat & 4.58679712391375 \tabularnewline
df & 297 \tabularnewline
p-value & 6.64443222905169e-06 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.82886622577225,4.57757549201916] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.34734248810557 \tabularnewline
df & 162 \tabularnewline
p-value & 0.0735165793361643 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.971846144948785,1.85890235586194] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232403&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]7.82822085889571[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]4.625[/C][/ROW]
[ROW][C]t-stat[/C][C]4.58679712391375[/C][/ROW]
[ROW][C]df[/C][C]297[/C][/ROW]
[ROW][C]p-value[/C][C]6.64443222905169e-06[/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][1.82886622577225,4.57757549201916][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.34734248810557[/C][/ROW]
[ROW][C]df[/C][C]162[/C][/ROW]
[ROW][C]p-value[/C][C]0.0735165793361643[/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][0.971846144948785,1.85890235586194][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232403&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232403&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 17.82822085889571
Mean of Sample 24.625
t-stat4.58679712391375
df297
p-value6.64443222905169e-06
H0 value0
Alternativetwo.sided
CI Level0.95
CI[1.82886622577225,4.57757549201916]
F-test to compare two variances
F-stat1.34734248810557
df162
p-value0.0735165793361643
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.971846144948785,1.85890235586194]







Welch Two Sample t-test (unpaired)
Mean of Sample 17.82822085889571
Mean of Sample 24.625
t-stat4.64870764509445
df296.684862511808
p-value5.03281625813645e-06
H0 value0
Alternativetwo.sided
CI Level0.95
CI[1.84716370162769,4.55927801616372]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 7.82822085889571 \tabularnewline
Mean of Sample 2 & 4.625 \tabularnewline
t-stat & 4.64870764509445 \tabularnewline
df & 296.684862511808 \tabularnewline
p-value & 5.03281625813645e-06 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.84716370162769,4.55927801616372] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232403&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]7.82822085889571[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]4.625[/C][/ROW]
[ROW][C]t-stat[/C][C]4.64870764509445[/C][/ROW]
[ROW][C]df[/C][C]296.684862511808[/C][/ROW]
[ROW][C]p-value[/C][C]5.03281625813645e-06[/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][1.84716370162769,4.55927801616372][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232403&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232403&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 17.82822085889571
Mean of Sample 24.625
t-stat4.64870764509445
df296.684862511808
p-value5.03281625813645e-06
H0 value0
Alternativetwo.sided
CI Level0.95
CI[1.84716370162769,4.55927801616372]







Wicoxon rank sum test with continuity correction (unpaired)
W14461
p-value4.50592978992786e-06
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.289741970407795
p-value7.8492062700608e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.312883435582822
p-value9.9256837227113e-07

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 14461 \tabularnewline
p-value & 4.50592978992786e-06 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.289741970407795 \tabularnewline
p-value & 7.8492062700608e-06 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.312883435582822 \tabularnewline
p-value & 9.9256837227113e-07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232403&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]14461[/C][/ROW]
[ROW][C]p-value[/C][C]4.50592978992786e-06[/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]0.289741970407795[/C][/ROW]
[ROW][C]p-value[/C][C]7.8492062700608e-06[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.312883435582822[/C][/ROW]
[ROW][C]p-value[/C][C]9.9256837227113e-07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232403&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232403&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)
W14461
p-value4.50592978992786e-06
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.289741970407795
p-value7.8492062700608e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.312883435582822
p-value9.9256837227113e-07



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')