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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 15:15:28 +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/t1418224826xlz39x8bt2e3bke.htm/, Retrieved Sun, 19 May 2024 15:37:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265356, Retrieved Sun, 19 May 2024 15:37:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63

Tree of Dependent Computations

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 11:18:40] [b98453cac15ba1066b407e146608df68]
- RMP   [Survey Scores] [] [2014-10-09 22:08:50] [32b17a345b130fdf5cc88718ed94a974]
- RMPD      [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-10 15:15:28] [023a69c6c348bca0f1811b046758af62] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
76	126
119	187
119	181
91	145
138	209
97	151
117	182
125	198
95	147
168	252
109	151
115	181
135	200
130	208
131	204
143	218
109	175
126	196
155	236
136	207
132	201
129	200
129	201
131	199
123	193
131	198
129	205
99	169
114	174
128	205
130	202
112	181
122	193
115	177
124	194
119	177
123	199
91	143
107	166
118	186
111	187
135	202
108	167
143	219
103	163
125	188
127	197
120	186
125	189
126	196
116	191
104	165
113	173
139	212
119	180
112	178
110	169
115	179
111	177
115	193
112	165
109	176
132	198
124	195
103	154
72	128
113	180
125	194
105	160
122	185
127	194
117	182
91	138
143	219
116	180
123	191
101	165
119	184
114	177
108	168
128	196
122	194
133	203
94	155
128	189
108	170
125	196
130	201
112	163
117	187
142	215
128	204
114	173
123	191
89	137
125	177
110	169
112	172
109	168
108	165
139	218
116	176
116	176
88	147
134	195
126	197
101	159
120	179
114	172
116	176
102	157
87	149
115	184
119	187
120	192
66	85
126	194
130	209
126	197
128	199
134	208
131	206
102	155
93	143
129	199
136	214
112	171
120	192
121	191
122	185
136	210
118	185
130	196
114	176
123	196
121	188
119	180
137	211
63	95
140	209
114	174
100	157
101	161
131	199
131	199
129	202
120	189
106	171
147	228
99	154
127	196
99	147
126	195
98	166
120	194
118	185
121	186
121	184
118	192
53	92
121	189
111	180
107	170
100	170
114	182
120	190
132	210
107	166
117	179
110	185
129	203
114	187
121	183
123	192
131	196
122	189
118	191
103	155
108	169
95	148
116	179
131	209
106	171
132	209
124	193
114	182
139	215
106	169
106	147
135	211
106	173
113	182
130	203
132	195
124	202
102	158
96	152
134	198
122	190
152	227
115	170
116	182
141	216
137	214
112	173
140	211
132	204
124	190
105	171
114	177
112	172
113	177
137	211
122	193
121	190
129	206
101	171
138	215
122	190
137	202
134	203
106	156
135	207
109	173
128	NA
147	NA
100	NA
132	NA
138	NA
114	NA
114	NA
118	NA
104	NA
135	NA
121	NA
128	NA
140	NA
92	NA
116	NA
118	NA
109	NA
139	NA
112	NA
75	NA
109	NA
101	NA
124	NA
117	NA
103	NA
130	NA
136	NA
140	NA
130	NA
118	NA
139	NA
102	NA
118	NA
104	NA
104	NA
111	NA
135	NA
130	NA
77	NA
132	NA
128	NA
136	NA
110	NA
120	NA
126	NA
133	NA
112	NA
103	NA
134	NA
124	NA

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=265356&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=265356&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265356&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 1118.467153284672
Mean of Sample 2183.875
t-stat-37.8483455692805
df496
p-value2.30875928513721e-148
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-68.8032555948897,-62.0124378357672]
F-test to compare two variances
F-stat0.459859487304372
df273
p-value1.14803562063753e-09
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.357286858646303,0.589981858762982]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 118.467153284672 \tabularnewline
Mean of Sample 2 & 183.875 \tabularnewline
t-stat & -37.8483455692805 \tabularnewline
df & 496 \tabularnewline
p-value & 2.30875928513721e-148 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-68.8032555948897,-62.0124378357672] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.459859487304372 \tabularnewline
df & 273 \tabularnewline
p-value & 1.14803562063753e-09 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.357286858646303,0.589981858762982] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265356&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]118.467153284672[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]183.875[/C][/ROW]
[ROW][C]t-stat[/C][C]-37.8483455692805[/C][/ROW]
[ROW][C]df[/C][C]496[/C][/ROW]
[ROW][C]p-value[/C][C]2.30875928513721e-148[/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][-68.8032555948897,-62.0124378357672][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.459859487304372[/C][/ROW]
[ROW][C]df[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]1.14803562063753e-09[/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][0.357286858646303,0.589981858762982][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265356&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265356&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 1118.467153284672
Mean of Sample 2183.875
t-stat-37.8483455692805
df496
p-value2.30875928513721e-148
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-68.8032555948897,-62.0124378357672]
F-test to compare two variances
F-stat0.459859487304372
df273
p-value1.14803562063753e-09
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.357286858646303,0.589981858762982]






Welch Two Sample t-test (unpaired)
Mean of Sample 1118.467153284672
Mean of Sample 2183.875
t-stat-36.4646864246824
df378.491948131193
p-value6.46048447127991e-126
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-68.9347732995676,-61.8809201310893]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 118.467153284672 \tabularnewline
Mean of Sample 2 & 183.875 \tabularnewline
t-stat & -36.4646864246824 \tabularnewline
df & 378.491948131193 \tabularnewline
p-value & 6.46048447127991e-126 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-68.9347732995676,-61.8809201310893] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265356&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]118.467153284672[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]183.875[/C][/ROW]
[ROW][C]t-stat[/C][C]-36.4646864246824[/C][/ROW]
[ROW][C]df[/C][C]378.491948131193[/C][/ROW]
[ROW][C]p-value[/C][C]6.46048447127991e-126[/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][-68.9347732995676,-61.8809201310893][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265356&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265356&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 1118.467153284672
Mean of Sample 2183.875
t-stat-36.4646864246824
df378.491948131193
p-value6.46048447127991e-126
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-68.9347732995676,-61.8809201310893]






Wicoxon rank sum test with continuity correction (unpaired)
W1074.5
p-value1.02778144994921e-76
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.941573253388947
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.111737486965589
p-value0.0921402553599345

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 1074.5 \tabularnewline
p-value & 1.02778144994921e-76 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.941573253388947 \tabularnewline
p-value & 0 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.111737486965589 \tabularnewline
p-value & 0.0921402553599345 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265356&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]1074.5[/C][/ROW]
[ROW][C]p-value[/C][C]1.02778144994921e-76[/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]0.941573253388947[/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]0.111737486965589[/C][/ROW]
[ROW][C]p-value[/C][C]0.0921402553599345[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265356&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265356&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)
W1074.5
p-value1.02778144994921e-76
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.941573253388947
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.111737486965589
p-value0.0921402553599345


Figures (Output of Computation)

Input Parameters & R Code

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