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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 computationThu, 11 Dec 2014 19:01:42 +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/11/t1418324606pt4wpdjblo0grpj.htm/, Retrieved Thu, 16 May 2024 04:50:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266289, Retrieved Thu, 16 May 2024 04:50:41 +0000
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-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2010-11-01 13:07:12] [b98453cac15ba1066b407e146608df68]
- RMP   [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-21 07:47:40] [32b17a345b130fdf5cc88718ed94a974]
- R PD      [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-11 19:01:42] [ec71b09431fe59ba6fc828a3f51756a9] [Current]
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Dataseries X:
0.56 12.9
0.79 7.4
0.68 12.2
0.66 12.8
0.37 7.4
0.71 6.7
0.35 12.6
0.55 14.8
0.76 13.3
0.49 11.1
0.56 8.2
0.60 11.4
0.44 6.4
0.55 10.6
0.58 12.0
0.40 6.3
0.42 11.3
0.58 11.9
0.64 9.3
0.58 9.6
0.44 10.0
0.46 6.4
0.64 13.8
0.59 10.8
0.54 13.8
0.71 11.7
0.20 10.9
0.89 16.1
0.55 13.4
0.71 9.9
0.48 11.5
0.49 8.3
0.58 11.7
0.78 6.1
0.71 9.0
0.51 9.7
0.65 10.8
0.68 10.3
0.24 10.4
0.36 12.7
0.65 9.3
0.79 11.8
0.67 5.9
0.74 11.4
0.72 13.0
0.73 10.8
0.58 12.3
0.67 11.3
0.43 11.8
0.59 7.9
0.43 12.7
0.80 12.3
0.74 11.6
0.43 6.7
0.72 10.9
0.50 12.1
0.45 13.3
0.88 10.1
0.67 5.7
0.32 14.3
0.20 8.0
0.84 13.3
0.83 9.3
0.65 12.5
0.74 7.6
0.53 15.9
0.58 9.2
0.65 9.1
0.64 11.1
0.60 13.0
0.52 14.5
0.53 12.2
0.73 12.3
0.52 11.4
0.61 8.8
0.73 14.6
0.79 7.3
0.29 12.6
0.86 NA
0.37 13.0
0.68 12.6
0.52 13.2
0.26 9.9
0.74 7.7
0.72 10.5
0.24 13.4
0.71 10.9
0.59 4.3
0.27 10.3
0.57 11.8
0.51 11.2
0.69 11.4
0.69 8.6
0.50 13.2
0.63 12.6
0.65 5.6
0.54 9.9
0.69 8.8
0.52 7.7
0.53 9.0
0.74 7.3
0.73 11.4
0.75 13.6
0.70 7.9
0.69 10.7
0.57 10.3
0.14 8.3
0.42 9.6
0.48 14.2
0.27 8.5
0.21 13.5
0.41 4.9
0.56 6.4
0.44 9.6
0.52 11.6
0.59 11.1
0.73 4.35
0.79 12.7
0.67 18.1
0.88 17.85
0.96 16.6
0.43 12.6
0.84 17.1
0.81 19.1
0.67 16.1
0.45 13.35
0.58 18.4
0.70 14.7
0.61 10.6
0.44 12.6
0.54 16.2
0.41 13.6
0.66 18.9
0.83 14.1
0.88 14.5
0.40 16.15
0.54 14.75
0.60 14.8
0.57 12.45
0.59 12.65
0.81 17.35
0.51 8.6
0.65 18.4
0.59 16.1
0.68 11.6
0.65 17.75
0.06 15.25
0.74 17.65
0.29 15.6
0.73 16.35
0.54 17.65
0.39 13.6
0.27 11.7
0.40 14.35
0.20 14.75
0.85 18.25
0.42 9.9
0.68 16
0.72 18.25
0.52 16.85
0.78 14.6
0.60 13.85
0.93 18.95
0.73 15.6
0.81 14.85
0.51 11.75
0.86 18.45
0.67 15.9
0.50 17.1
0.74 16.1
0.85 19.9
0.75 10.95
0.83 18.45
0.82 15.1
0.58 15
0.72 11.35
0.89 15.95
0.51 18.1
0.75 14.6
0.84 15.4
0.84 15.4
0.59 17.6
0.64 13.35
0.45 19.1
0.57 15.35
0.58 7.6
0.72 13.4
0.38 13.9
0.68 19.1
0.45 15.25
0.55 12.9
0.73 16.1
0.73 17.35
0.73 13.15
0.71 12.15
0.38 12.6
0.79 10.35
0.32 15.4
0.62 9.6
0.42 18.2
0.45 13.6
0.97 14.85
0.67 14.75
0.08 14.1
0.49 14.9
0.66 16.25
0.67 19.25
0.55 13.6
0.55 13.6
0.49 15.65
0.56 12.75
0.69 14.6
0.47 9.85
0.68 12.65
0.43 11.9
0.00 19.2
0.48 16.6
0.77 11.2
0.71 15.25
0.43 11.9
0.50 13.2
0.68 16.35
0.34 12.4
0.47 15.85
0.33 14.35
0.80 18.15
0.74 11.15
0.82 15.65
0.57 17.75
0.46 7.65
0.91 12.35
0.41 15.6
0.64 19.3
0.58 15.2
0.45 17.1
0.77 15.6
0.67 18.4
0.53 19.05
0.07 18.55
0.65 19.1
0.76 13.1
0.56 12.85
0.07 9.5
0.72 4.5
0.61 11.85
0.47 13.6
0.06 11.7
0.37 12.4
0.76 13.35
0.47 11.4
0.55 14.9
0.85 19.9
0.77 17.75
0.79 11.2
0.70 14.6
0.46 17.6
0.51 14.05
0.65 16.1
0.57 13.35
0.68 11.85
0.52 11.95
0.70 14.75
0.46 15.15
0.88 13.2
0.76 16.85
0.74 7.85
0.56 7.7
0.47 12.6
0.44 7.85
0.75 10.95
0.78 12.35
0.26 9.95
0.55 14.9
0.49 16.65
0.81 13.4
0.45 13.95
0.39 15.7
0.89 16.85
0.66 10.95
0.34 15.35
0.84 12.2
0.05 15.1
0.79 17.75
0.60 15.2
0.69 14.6
0.58 16.65
0.66 8.1




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=266289&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=266289&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266289&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'Sir Maurice George Kendall' @ kendall.wessa.net







Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.3455594405594
t-stat-61.3057222539244
df285
p-value3.49952889053369e-166
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-12.741934245398,-11.9491846357208]
F-test to compare two variances
F-stat0.00286249621023279
df286
p-value6.24792278475836e-280
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.00226871304963992,0.00361151523260147]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -12.3455594405594 \tabularnewline
t-stat & -61.3057222539244 \tabularnewline
df & 285 \tabularnewline
p-value & 3.49952889053369e-166 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-12.741934245398,-11.9491846357208] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.00286249621023279 \tabularnewline
df & 286 \tabularnewline
p-value & 6.24792278475836e-280 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.00226871304963992,0.00361151523260147] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266289&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-12.3455594405594[/C][/ROW]
[ROW][C]t-stat[/C][C]-61.3057222539244[/C][/ROW]
[ROW][C]df[/C][C]285[/C][/ROW]
[ROW][C]p-value[/C][C]3.49952889053369e-166[/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][-12.741934245398,-11.9491846357208][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.00286249621023279[/C][/ROW]
[ROW][C]df[/C][C]286[/C][/ROW]
[ROW][C]p-value[/C][C]6.24792278475836e-280[/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][0.00226871304963992,0.00361151523260147][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266289&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266289&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 (paired)
Difference: Mean1 - Mean2-12.3455594405594
t-stat-61.3057222539244
df285
p-value3.49952889053369e-166
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-12.741934245398,-11.9491846357208]
F-test to compare two variances
F-stat0.00286249621023279
df286
p-value6.24792278475836e-280
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.00226871304963992,0.00361151523260147]







Welch Two Sample t-test (paired)
Difference: Mean1 - Mean2-12.3455594405594
t-stat-61.3057222539244
df285
p-value3.49952889053369e-166
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-12.741934245398,-11.9491846357208]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & -12.3455594405594 \tabularnewline
t-stat & -61.3057222539244 \tabularnewline
df & 285 \tabularnewline
p-value & 3.49952889053369e-166 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-12.741934245398,-11.9491846357208] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266289&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]-12.3455594405594[/C][/ROW]
[ROW][C]t-stat[/C][C]-61.3057222539244[/C][/ROW]
[ROW][C]df[/C][C]285[/C][/ROW]
[ROW][C]p-value[/C][C]3.49952889053369e-166[/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][-12.741934245398,-11.9491846357208][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266289&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266289&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 (paired)
Difference: Mean1 - Mean2-12.3455594405594
t-stat-61.3057222539244
df285
p-value3.49952889053369e-166
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-12.741934245398,-11.9491846357208]







Wicoxon rank sum test with continuity correction (paired)
W0
p-value1.19309733672401e-48
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic1
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.458066323919982
p-value0

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 0 \tabularnewline
p-value & 1.19309733672401e-48 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 1 \tabularnewline
p-value & 0 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.458066323919982 \tabularnewline
p-value & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266289&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]0[/C][/ROW]
[ROW][C]p-value[/C][C]1.19309733672401e-48[/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]1[/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]0.458066323919982[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266289&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266289&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 (paired)
W0
p-value1.19309733672401e-48
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic1
p-value0
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.458066323919982
p-value0



Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = .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 <- '.95'
par2 <- '2'
par1 <- '1'
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')