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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 computationMon, 15 Dec 2014 15:37:55 +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/15/t1418657897ukva6v73lrptga1.htm/, Retrieved Thu, 16 May 2024 11:05:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268648, Retrieved Thu, 16 May 2024 11:05:49 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Percentiles] [Intrinsic Motivat...] [2010-10-12 12:10:58] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kernel Density Estimation] [] [2011-10-18 22:42:23] [b98453cac15ba1066b407e146608df68]
- RMPD    [Percentiles] [] [2011-10-18 22:46:45] [b98453cac15ba1066b407e146608df68]
- RMPD      [Notched Boxplots] [] [2011-10-18 22:58:56] [b98453cac15ba1066b407e146608df68]
- RM D        [Back to Back Histogram] [] [2011-10-18 23:05:48] [b98453cac15ba1066b407e146608df68]
- RMPD          [Back to Back Histogram] [] [2014-12-09 17:55:01] [ea990983fba95a758c0bb6d29c9aee24]
-   P             [Back to Back Histogram] [] [2014-12-09 18:09:27] [ea990983fba95a758c0bb6d29c9aee24]
- RMPD                [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-15 15:37:55] [6260c34aa94cecca073345f42e0d4b5d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
74	114
115	133
90	94
120	113
128	92
141	161
129	103
122	110
148	131
125	127
107	106
125	114
98	130
110	127
122	125
121	126
131	119
139	119
114	125
105	125
124	125
111	108
109	118
133	113
97	116
105	115
112	89
112	105
113	116
107	109
129	93
100	104
111	125
124	108
120	128
97	110
137	99
121	135
123	122
95	125
132	116
137	108
110	123
110	100
117	103
120	114
115	110
127	117
106	107
116	107
113	95
87	118
123	125
126	118
111	123
118	109
85	97
106	134
111	101
104	119
136	122
87	104
124	134
117	122
104	93
107	130
98	117
96	122
121	99
123	71
126	110
109	121
86	105
110	101
105	123
95	138
126	112
115	118
120	99
126	115
124	138
124	111
90	102
115	120
106	128
109	92
125	121
121	105
111	121
107	108
114	86
129	114
129	138
129	125
89	122
113	105
132	114
137	112
117	123
107	120
118	127
115	122
125	115
110	110
124	117
134	148
130	121
102	111
95	113
126	122
119	100
79	107
120	118
141	93
122	122
124	105
113	139
83	114
149	93
129	60
122	108
122	125
96	123
124	85
125	116
118	120
52	117
120	125
114	100
123	95
97	127
119	113
104	108
114	117
106	128
111	132
114	143
105	119
112	119
129	114
105	131
126	59
120	128
111	116
132	111
105	104
111	131
114	98
128	128
122	124
117	112
119	104
109	126
112	94
116	97
114	91
134	121
132	104
125	129
87	127
120	120
109	120
112	108
133	122
102	99
118	96
119	115
122	116
105	115
126	116
99	109
110	104
134	110
135	116
121	127
104	126
132	116
129	119
142	126
107	119
123	101
124	92
143	137
115	104
107	104
133	134
113	98
132	112
114	128
136	100
141	93
126	130
112	148
104	103
135	110
105	135
121	128
113	104
103	102
125	108
125	116
116	111
122	137
155	108
112	121
135	118
114	109
124	130
124	111
136	129
124	120
124	126
129	128
104	124
137	98
116	128
123	143
	119
	113
	103
	131
	100
	101
	131
	117
	125
	89
	98
	115
	127
	101
	108
	127
	74
	115
	99
	136
	112
	99
	124
	125
	132
	126
	124
	97
	134
	126
	116
	98
	113
	125
	99
	100
	109
	130
	131
	105
	122
	140
	133
	127
	143
	75
	128
	108
	132
	107
	111
	149
	71
	116
	122
	136
	115
	120
	108
	99
	133
	112
	132
	120

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268648&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]2 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=268648&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268648&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 1116.615658362989
Mean of Sample 2114.964412811388
t-stat1.34674154713867
df560
p-value0.178608259474003
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.757079718815481,4.05957082201832]
F-test to compare two variances
F-stat1.02664067671436
df280
p-value0.826046299971435
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.811844742314632,1.2982668041669]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 116.615658362989 \tabularnewline
Mean of Sample 2 & 114.964412811388 \tabularnewline
t-stat & 1.34674154713867 \tabularnewline
df & 560 \tabularnewline
p-value & 0.178608259474003 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.757079718815481,4.05957082201832] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.02664067671436 \tabularnewline
df & 280 \tabularnewline
p-value & 0.826046299971435 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.811844742314632,1.2982668041669] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268648&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]116.615658362989[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]114.964412811388[/C][/ROW]
[ROW][C]t-stat[/C][C]1.34674154713867[/C][/ROW]
[ROW][C]df[/C][C]560[/C][/ROW]
[ROW][C]p-value[/C][C]0.178608259474003[/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][-0.757079718815481,4.05957082201832][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.02664067671436[/C][/ROW]
[ROW][C]df[/C][C]280[/C][/ROW]
[ROW][C]p-value[/C][C]0.826046299971435[/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][0.811844742314632,1.2982668041669][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268648&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268648&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 1116.615658362989
Mean of Sample 2114.964412811388
t-stat1.34674154713867
df560
p-value0.178608259474003
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.757079718815481,4.05957082201832]
F-test to compare two variances
F-stat1.02664067671436
df280
p-value0.826046299971435
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.811844742314632,1.2982668041669]






Welch Two Sample t-test (unpaired)
Mean of Sample 1116.615658362989
Mean of Sample 2114.964412811388
t-stat1.34674154713867
df559.903250220681
p-value0.178608353566476
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.75708062015175,4.05957172335459]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 116.615658362989 \tabularnewline
Mean of Sample 2 & 114.964412811388 \tabularnewline
t-stat & 1.34674154713867 \tabularnewline
df & 559.903250220681 \tabularnewline
p-value & 0.178608353566476 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.75708062015175,4.05957172335459] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268648&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]116.615658362989[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]114.964412811388[/C][/ROW]
[ROW][C]t-stat[/C][C]1.34674154713867[/C][/ROW]
[ROW][C]df[/C][C]559.903250220681[/C][/ROW]
[ROW][C]p-value[/C][C]0.178608353566476[/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][-0.75708062015175,4.05957172335459][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268648&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268648&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 1116.615658362989
Mean of Sample 2114.964412811388
t-stat1.34674154713867
df559.903250220681
p-value0.178608353566476
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.75708062015175,4.05957172335459]






Wicoxon rank sum test with continuity correction (unpaired)
W42639
p-value0.100743521892359
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0818505338078292
p-value0.303345602245867
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0569395017793594
p-value0.752478418565335

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 42639 \tabularnewline
p-value & 0.100743521892359 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.0818505338078292 \tabularnewline
p-value & 0.303345602245867 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0569395017793594 \tabularnewline
p-value & 0.752478418565335 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268648&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]42639[/C][/ROW]
[ROW][C]p-value[/C][C]0.100743521892359[/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]0.0818505338078292[/C][/ROW]
[ROW][C]p-value[/C][C]0.303345602245867[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0569395017793594[/C][/ROW]
[ROW][C]p-value[/C][C]0.752478418565335[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268648&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268648&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)
W42639
p-value0.100743521892359
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0818505338078292
p-value0.303345602245867
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0569395017793594
p-value0.752478418565335


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')