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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 computationWed, 16 Nov 2011 11:27:58 -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/2011/Nov/16/t1321460955wdkh0bo41fe5jxr.htm/, Retrieved Thu, 28 Mar 2024 09:53:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=144097, Retrieved Thu, 28 Mar 2024 09:53:07 +0000
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Estimated Impact82
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:23:25] [b98453cac15ba1066b407e146608df68]
- RMPD  [Paired and Unpaired Two Samples Tests about the Mean] [Minitutorial 1] [2010-11-15 22:34:03] [b8e188bcc949964bed729335b3416734]
-    D      [Paired and Unpaired Two Samples Tests about the Mean] [hypothese 1] [2011-11-16 16:27:58] [9c3f7eb531442757fa35fbfef7e48a65] [Current]
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Dataseries X:
4	5	3	5
4	3	4	4
4	3	4	4
4	4	2	4
4	2	5	3
5	1	5	4
3	2	5	5
4	4	2	4
4	5	4	3
4	5	3	4
5	5	4	5
3	3	4	4
5	4	3	5
5	2	5	4
2	4	2	4
3	5	2	3
5	4	3	4
3	5	2	4
4	4	2	5
4	2	4	2
3	5	2	4
4	2	5	2
4	2	5	4
5	4	2	4
5	4	5	4
5	1	5	4
3	4	4	4
4	3	4	3
4	3	4	4
2	4	3	4
3		4	4
4	4	2	5
4	2	4	3
4	3	3	4
5	2	2	4
2	4	2	4
3	4	1	4
4	3	2	4
3	3	4	3
4	4	2	4
4	4	4	5
3	4	2	4
4	4	3	4
5	3	4	2
4	4	4	4
4	4	4	3
4	4	2	4
4	4	3	4
4	5	3	4
3	4	3	5
4	4	3	2
3	3	2	4
4	4	3	5
3	4	4	4
4	3	5	3
2	5	5	4
4	3	4	4
4	4	3	4
3	4	3	4
4	4	2	4
3	2	1	3
5	3	4	3
3	4	1	3
5	4	3	2
5	3	2	3
4	4	4	3
3	4	3	4
3	4	2	4
4	4	3	4
4	4	2	4
4	4	2	4
3	4	4	3
4	5	2	4
4	3	3	5
4	4	2	4
4	3	4	5
4	5	2	4
3	3	2	4
4	4	4	2
3	3	2	4
4	4	2	4
4	4	3	4
3	4	2	4
5	4	2	4
3	4	2	3
5	4	2	3
4	3	3	4
4	4	3	4
3	4	3	3
2	4	3	4
3	4	1	4
1	3	4	5
4	4	3	5
4	2	4	3
4	4	2	4
4	5	1	5
4	3	4	4
5	4	4	3
3	3	3	4
2	5	2	5
4	3	4	4
3	4	4	5
4	4	4	4
4	3	2	2
4	5	3	3
4	3	4	5
4	4	2	4
2	4	5	5
4	4	2	4
5	3	5	5
4	4	2	3
4	4	4	3
4	4	2	4
3	5	2	3
4	4	4	4
4	3	4	4
3	4	2	4
2	4	4	2
4	4	4	3
5	2	2	5
4	3	4	1
4	4	4	4
5	4	4	4
5	5	4	4
2	3	5	5
3	4	1	4
4	4	4	5
4	4	4	5
4	4	3	4
4	3	3	4
3	5	1	4
3	3	1	4
4	4	3	4
3	4	2	4
4	5	2	5
5	3	4	3
4	3	2	3
3	3	2	4
2	4	2	4
5	3	4	3
3	4	2	4
4	3	4	3
2	4	2	4
4	4	4	2
3	2	2	4
4	4	4	4
3	4	4	4
4	4	4	4
4	2	4	4
4	2	4	4
5	4	4	5
5	4	3	5
3	4	4	4
3	4	2	4
	4	3	5
3	4	4	4
1	3	4	5
4	3	2	4
4	4	3	4
4	4	3	3
4	4	4	4
2	4	2	5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.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=144097&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]'Herman Ole Andreas Wold' @ wold.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=144097&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144097&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 13.71604938271605
Mean of Sample 23.12345679012346
t-stat5.53958141709624
df322
p-value6.30830363786394e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.382135874502369,0.803049310682816]
F-test to compare two variances
F-stat0.466456387237656
df161
p-value1.80608730483397e-06
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.342110680689495,0.635997568846109]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 3.71604938271605 \tabularnewline
Mean of Sample 2 & 3.12345679012346 \tabularnewline
t-stat & 5.53958141709624 \tabularnewline
df & 322 \tabularnewline
p-value & 6.30830363786394e-08 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.382135874502369,0.803049310682816] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.466456387237656 \tabularnewline
df & 161 \tabularnewline
p-value & 1.80608730483397e-06 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.342110680689495,0.635997568846109] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144097&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]3.71604938271605[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]3.12345679012346[/C][/ROW]
[ROW][C]t-stat[/C][C]5.53958141709624[/C][/ROW]
[ROW][C]df[/C][C]322[/C][/ROW]
[ROW][C]p-value[/C][C]6.30830363786394e-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][0.382135874502369,0.803049310682816][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.466456387237656[/C][/ROW]
[ROW][C]df[/C][C]161[/C][/ROW]
[ROW][C]p-value[/C][C]1.80608730483397e-06[/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][0.342110680689495,0.635997568846109][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144097&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144097&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 13.71604938271605
Mean of Sample 23.12345679012346
t-stat5.53958141709624
df322
p-value6.30830363786394e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.382135874502369,0.803049310682816]
F-test to compare two variances
F-stat0.466456387237656
df161
p-value1.80608730483397e-06
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.342110680689495,0.635997568846109]







Welch Two Sample t-test (unpaired)
Mean of Sample 13.71604938271605
Mean of Sample 23.12345679012346
t-stat5.53958141709624
df284.358435670737
p-value6.90699365992271e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.382030723586782,0.803154461598403]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 3.71604938271605 \tabularnewline
Mean of Sample 2 & 3.12345679012346 \tabularnewline
t-stat & 5.53958141709624 \tabularnewline
df & 284.358435670737 \tabularnewline
p-value & 6.90699365992271e-08 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.382030723586782,0.803154461598403] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144097&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]3.71604938271605[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]3.12345679012346[/C][/ROW]
[ROW][C]t-stat[/C][C]5.53958141709624[/C][/ROW]
[ROW][C]df[/C][C]284.358435670737[/C][/ROW]
[ROW][C]p-value[/C][C]6.90699365992271e-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][0.382030723586782,0.803154461598403][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144097&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144097&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 13.71604938271605
Mean of Sample 23.12345679012346
t-stat5.53958141709624
df284.358435670737
p-value6.90699365992271e-08
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.382030723586782,0.803154461598403]







Wicoxon rank sum test with continuity correction (unpaired)
W16977
p-value1.19370462169352e-06
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.283950617283951
p-value4.2500440324833e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.333333333333333
p-value3.04599594436183e-08

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 16977 \tabularnewline
p-value & 1.19370462169352e-06 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.283950617283951 \tabularnewline
p-value & 4.2500440324833e-06 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.333333333333333 \tabularnewline
p-value & 3.04599594436183e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144097&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]16977[/C][/ROW]
[ROW][C]p-value[/C][C]1.19370462169352e-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]0.283950617283951[/C][/ROW]
[ROW][C]p-value[/C][C]4.2500440324833e-06[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.333333333333333[/C][/ROW]
[ROW][C]p-value[/C][C]3.04599594436183e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144097&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144097&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)
W16977
p-value1.19370462169352e-06
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.283950617283951
p-value4.2500440324833e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.333333333333333
p-value3.04599594436183e-08



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')