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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 computationFri, 26 Oct 2012 07:35:15 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Oct/26/t1351251595dillvld7xjicn1c.htm/, Retrieved Tue, 10 Feb 2026 18:28:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=183960, Retrieved Tue, 10 Feb 2026 18:28:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact369

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] [test] [2012-10-26 10:44:09] [f8950b13b9b6c1e097d81f3c7491f9a1]
- R PD  [Paired and Unpaired Two Samples Tests about the Mean] [Two-Sample T-test...] [2012-10-26 11:02:58] [f8950b13b9b6c1e097d81f3c7491f9a1]
-    D      [Paired and Unpaired Two Samples Tests about the Mean] [Two-Sample T-test...] [2012-10-26 11:35:15] [09cdab5d933081235930b6410ef38881] [Current]
-    D        [Paired and Unpaired Two Samples Tests about the Mean] [Two-Sample T-test...] [2012-10-26 11:53:05] [f8950b13b9b6c1e097d81f3c7491f9a1]
-   P           [Paired and Unpaired Two Samples Tests about the Mean] [Two-Sample T-test...] [2012-10-26 12:19:30] [f8950b13b9b6c1e097d81f3c7491f9a1]
- RMP           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [test] [2012-10-26 12:37:49] [f8950b13b9b6c1e097d81f3c7491f9a1]
- RM              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 12:41:18] [f8950b13b9b6c1e097d81f3c7491f9a1]
- R  D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 12:49:47] [f8950b13b9b6c1e097d81f3c7491f9a1]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 12:59:00] [f8950b13b9b6c1e097d81f3c7491f9a1]
-                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 13:20:52] [f8950b13b9b6c1e097d81f3c7491f9a1]
-   P                   [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Deel 3: ANOVA en ...] [2012-12-19 23:31:36] [5e6119a0aa181aac6bb71d6b937f8665]
-  M                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 13:22:32] [f8950b13b9b6c1e097d81f3c7491f9a1]
-                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 13:23:33] [f8950b13b9b6c1e097d81f3c7491f9a1]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 13:48:59] [f8950b13b9b6c1e097d81f3c7491f9a1]
-                         [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [1-way ANOVA Quest...] [2012-10-26 13:59:27] [f8950b13b9b6c1e097d81f3c7491f9a1]
- RM D                      [Two-Way ANOVA] [2-Way Anova - Exp...] [2012-10-26 14:07:12] [f8950b13b9b6c1e097d81f3c7491f9a1]
- R PD                        [Two-Way ANOVA] [Anova deel 2] [2012-12-22 02:55:00] [74be16979710d4c4e7c6647856088456]
-   PD                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Deel 3: ANOVA en ...] [2012-12-19 23:04:28] [5e6119a0aa181aac6bb71d6b937f8665]
-   PD        [Paired and Unpaired Two Samples Tests about the Mean] [Two-Sample T-test...] [2012-10-26 12:18:10] [f8950b13b9b6c1e097d81f3c7491f9a1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	4	0	2	'T'
1	1	0	0	2	'T'
0	1	4	1	1,5	'T'
0	0	0	0	0	'T'
1	1	0	1	1	'T'
1	1	0	1	2	'T'
1	1	0	1	2	'T'
0	1	0	1	1	'T'
0	1	4	1	2	'T'
1	1	1	0	2	'T'
0	0	4	0	2	'T'
0	1	0	1	0	'T'
0	1	2	1	0	'T'
0	1	0	0	2	'T'
0	0	0	NA	NA	'T'
1	1	0	1	2	'T'
1	1	1	0	2	'T'
1	1	0	1	0,5	'T'
0	1	0	1	2	'T'
0	0	2	1	0	'T'
1	1	2	1	2	'T'
1	1	1	0	0	'T'
0	0	2	NA	NA	'T'
1	0	0	NA	NA	'T'
1	1	3	1	2	'T'
1	0	0	1	0	'T'
1	1	0	NA	NA	'T'
0	0	0	NA	NA	'T'
0	0	1	0	2	'T'
1	1	0	1	1	'T'
1	0	0	0	0,5	'T'
1	1	4	0	2	'T'
0	0	0	1	0,5	'T'
0	0	1	NA	NA	'T'
0	0	0	1	0,5	'T'
1	1	0	NA	NA	'T'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183960&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]3 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=183960&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183960&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 time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.111111111111111
t-stat-1.27589457900886
df35
p-value0.210395524095103
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.287902792253449,0.065680570031227]
F-test to compare two variances
F-stat1.08026755852843
df35
p-value0.820631121275098
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.550850737945888,2.11850128831743]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -0.111111111111111 \tabularnewline
t-stat & -1.27589457900886 \tabularnewline
df & 35 \tabularnewline
p-value & 0.210395524095103 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.287902792253449,0.065680570031227] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.08026755852843 \tabularnewline
df & 35 \tabularnewline
p-value & 0.820631121275098 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.550850737945888,2.11850128831743] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183960&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-0.111111111111111[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.27589457900886[/C][/ROW]
[ROW][C]df[/C][C]35[/C][/ROW]
[ROW][C]p-value[/C][C]0.210395524095103[/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][-0.287902792253449,0.065680570031227][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.08026755852843[/C][/ROW]
[ROW][C]df[/C][C]35[/C][/ROW]
[ROW][C]p-value[/C][C]0.820631121275098[/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][0.550850737945888,2.11850128831743][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183960&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183960&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 (paired)
Difference: Mean1 - Mean2-0.111111111111111
t-stat-1.27589457900886
df35
p-value0.210395524095103
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.287902792253449,0.065680570031227]
F-test to compare two variances
F-stat1.08026755852843
df35
p-value0.820631121275098
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.550850737945888,2.11850128831743]






Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-0.111111111111111
t-stat-1.27589457900886
df35
p-value0.210395524095103
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.287902792253449,0.065680570031227]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -0.111111111111111 \tabularnewline
t-stat & -1.27589457900886 \tabularnewline
df & 35 \tabularnewline
p-value & 0.210395524095103 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.287902792253449,0.065680570031227] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183960&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-0.111111111111111[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.27589457900886[/C][/ROW]
[ROW][C]df[/C][C]35[/C][/ROW]
[ROW][C]p-value[/C][C]0.210395524095103[/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][-0.287902792253449,0.065680570031227][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183960&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183960&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 (paired)
Difference: Mean1 - Mean2-0.111111111111111
t-stat-1.27589457900886
df35
p-value0.210395524095103
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.287902792253449,0.065680570031227]






Wicoxon rank sum test with continuity correction (paired)
W16.5
p-value0.227272320646642
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.111111111111111
p-value0.97936311445764
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.527777777777778
p-value8.83123498954808e-05

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 16.5 \tabularnewline
p-value & 0.227272320646642 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.111111111111111 \tabularnewline
p-value & 0.97936311445764 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.527777777777778 \tabularnewline
p-value & 8.83123498954808e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183960&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]16.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.227272320646642[/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]0.111111111111111[/C][/ROW]
[ROW][C]p-value[/C][C]0.97936311445764[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.527777777777778[/C][/ROW]
[ROW][C]p-value[/C][C]8.83123498954808e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183960&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183960&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 (paired)
W16.5
p-value0.227272320646642
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.111111111111111
p-value0.97936311445764
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.527777777777778
p-value8.83123498954808e-05


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 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')