FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 08 Dec 2014 15:01:02 +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/08/t1418050978t85rs2d3lx1lcps.htm/, Retrieved Sun, 19 May 2024 08:46:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264040, Retrieved Sun, 19 May 2024 08:46:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73

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] [] [2014-12-08 15:01:02] [003c997d057e54927bd887526d955d96] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0 26 50
1 57 62
0 37 54
1 67 71
1 43 54
1 52 65
0 52 73
1 43 52
1 84 84
1 67 42
1 49 66
1 70 65
1 52 78
0 58 73
0 68 75
0 62 72
1 43 66
0 56 70
1 56 61
0 74 81
1 65 71
1 63 69
0 58 71
1 57 72
1 63 68
1 53 70
1 57 68
0 51 61
1 64 67
0 53 76
0 29 70
0 54 60
1 58 72
1 43 69
1 51 71
1 53 62
0 54 70
1 56 64
1 61 58
0 47 76
1 39 52
1 48 59
1 50 68
1 35 76
1 30 65
0 68 67
1 49 59
1 61 69
0 67 76
1 47 63
1 56 75
1 50 63
1 43 60
1 67 73
1 62 63
1 57 70
0 41 75
1 54 66
0 45 63
1 48 63
1 61 64
0 56 70
0 41 75
1 43 61
0 53 60
1 44 62
0 66 73
1 58 61
1 46 66
0 37 64
0 51 59
0 51 64
0 56 60
1 66 56
0 37 78
1 59 53
0 42 67
1 38 59
0 66 66
0 34 68
1 53 71
0 49 66
0 55 73
0 49 72
1 59 71
0 40 59
1 58 64
1 60 66
0 63 78
0 56 68
0 54 73
1 52 62
1 34 65
1 69 68
0 32 65
1 48 60
0 67 71
1 58 65
1 57 68
1 42 64
1 64 74
1 58 69
0 66 76
1 26 68
1 61 72
1 52 67
0 51 63
0 55 59
0 50 73
0 60 66
0 56 62
0 63 69
1 61 66
1 52 51
1 16 56
1 46 67
1 56 69
0 52 57
1 55 56
1 50 55
0 59 63
1 60 67
0 52 65
0 44 47
1 67 76
1 52 64
1 55 68
1 37 64
1 54 65
1 72 71
1 51 63
1 48 60
0 60 68
1 50 72
1 63 70
1 33 61
1 67 61
1 46 62
1 54 71
0 59 71
1 61 51
1 33 56
1 47 70
1 69 73
1 52 76
0 55 68
0 41 48
1 73 52
0 52 60
0 50 59
1 51 57
0 60 79
1 56 60
1 56 60
0 29 59
1 66 62
1 66 59
1 73 61
0 55 71
0 64 57
0 40 66
0 46 63
1 58 69
0 43 58
1 61 59
0 51 48
1 50 66
0 52 73
1 54 67
0 66 61
0 61 68
1 80 75
0 51 62
1 56 69
1 56 58
1 56 60
1 53 74
1 47 55
0 25 62
1 47 63
0 46 69
0 50 58
0 39 58
1 51 68
0 58 72
1 35 62
0 58 62
0 60 65
0 62 69
0 63 66
1 53 72
1 46 62
1 67 75
1 59 58
0 64 66
0 38 55
1 50 47
0 48 72
0 48 62
0 47 64
0 66 64
1 47 19
1 63 50
0 58 68
0 44 70
1 51 79
0 43 69
1 55 71
1 38 48
0 45 73
1 50 74
1 54 66
1 57 71
0 60 74
0 55 78
0 56 75
1 49 53
1 37 60
1 59 70
1 46 69
0 51 65
0 58 78
0 64 78
1 53 59
1 48 72
0 51 70
0 47 63
0 59 63
1 62 71
1 62 74
0 51 67
0 64 66
0 52 62
1 67 80
1 50 73
1 54 67
1 58 61
0 56 73
1 63 74
1 31 32
1 65 69
0 71 69
0 50 84
1 57 64
0 47 58
1 47 59
1 57 78
0 43 57
1 41 60
0 63 68
1 63 68
1 56 73
0 51 69
1 50 67
0 22 60
1 41 65
0 59 66
1 56 74
0 66 81
0 53 72
1 42 55
1 52 49
0 54 74
1 44 53
1 62 64
0 53 65
1 50 57
0 36 51
0 76 80
1 66 67
1 62 70
0 59 74
1 47 75
0 55 70
0 58 69
1 60 65
0 44 55
0 57 71
1 45 65

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'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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264040&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264040&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264040&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'Gertrude Mary Cox' @ cox.wessa.net






Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.3440860215054
t-stat-19.2508358117814
df278
p-value4.54815121191676e-53
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.606356031847,-11.0818160111638]
F-test to compare two variances
F-stat1.58706342347619
df278
p-value0.000128017366025412
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.25395295902516,2.00866411455663]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -12.3440860215054 \tabularnewline
t-stat & -19.2508358117814 \tabularnewline
df & 278 \tabularnewline
p-value & 4.54815121191676e-53 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-13.606356031847,-11.0818160111638] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.58706342347619 \tabularnewline
df & 278 \tabularnewline
p-value & 0.000128017366025412 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [1.25395295902516,2.00866411455663] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264040&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-12.3440860215054[/C][/ROW]
[ROW][C]t-stat[/C][C]-19.2508358117814[/C][/ROW]
[ROW][C]df[/C][C]278[/C][/ROW]
[ROW][C]p-value[/C][C]4.54815121191676e-53[/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][-13.606356031847,-11.0818160111638][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.58706342347619[/C][/ROW]
[ROW][C]df[/C][C]278[/C][/ROW]
[ROW][C]p-value[/C][C]0.000128017366025412[/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][1.25395295902516,2.00866411455663][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264040&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264040&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 - Mean2-12.3440860215054
t-stat-19.2508358117814
df278
p-value4.54815121191676e-53
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.606356031847,-11.0818160111638]
F-test to compare two variances
F-stat1.58706342347619
df278
p-value0.000128017366025412
H0 value1
Alternativetwo.sided
CI Level0.95
CI[1.25395295902516,2.00866411455663]






Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.3440860215054
t-stat-19.2508358117814
df278
p-value4.54815121191676e-53
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.606356031847,-11.0818160111638]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -12.3440860215054 \tabularnewline
t-stat & -19.2508358117814 \tabularnewline
df & 278 \tabularnewline
p-value & 4.54815121191676e-53 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-13.606356031847,-11.0818160111638] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264040&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-12.3440860215054[/C][/ROW]
[ROW][C]t-stat[/C][C]-19.2508358117814[/C][/ROW]
[ROW][C]df[/C][C]278[/C][/ROW]
[ROW][C]p-value[/C][C]4.54815121191676e-53[/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][-13.606356031847,-11.0818160111638][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264040&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264040&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 - Mean2-12.3440860215054
t-stat-19.2508358117814
df278
p-value4.54815121191676e-53
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-13.606356031847,-11.0818160111638]






Wicoxon rank sum test with continuity correction (paired)
W1814.5
p-value4.94896892074256e-39
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.551971326164875
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.100358422939068
p-value0.12037939683337

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 1814.5 \tabularnewline
p-value & 4.94896892074256e-39 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.551971326164875 \tabularnewline
p-value & 0 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.100358422939068 \tabularnewline
p-value & 0.12037939683337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264040&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]1814.5[/C][/ROW]
[ROW][C]p-value[/C][C]4.94896892074256e-39[/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]0.551971326164875[/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]0.100358422939068[/C][/ROW]
[ROW][C]p-value[/C][C]0.12037939683337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264040&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264040&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)
W1814.5
p-value4.94896892074256e-39
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.551971326164875
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.100358422939068
p-value0.12037939683337


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 3 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0 ;
Parameters (R input):
par1 = 2 ; par2 = 3 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0 ;
R code (references can be found in the software module):
par6 <- ''
par5 <- 'paired'
par4 <- 'two.sided'
par3 <- '0,95'
par2 <- '3'
par1 <- '2'
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')