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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, 12 Dec 2016 16:14:01 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/12/t1481557498annufpxkrgh75f6.htm/, Retrieved Fri, 01 Nov 2024 03:43:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298924, Retrieved Fri, 01 Nov 2024 03:43:33 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

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-       [Paired and Unpaired Two Samples Tests about the Mean] [Unpaired two samp...] [2016-12-12 15:14:01] [168e69cfb1c001c8b9ca70e943ef53ff] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2	3	4		4	3	3
2	1	4		5	4	4
2	5	4		4	5	5
3	4	4		NA	4	4
4	3	3		NA	4	4
3	2	5		5	3	5
4	4	4		5	3	5
2	5	4		NA	4	5
NA	5	2		NA	4	5
4	3	4		5	4	5
2	2	4		5	4	5
2	2	3		4	4	4
5	4	3		4	4	4
4	4	4		4	3	4
2	4	4		4	4	4
3	5	4		5	4	5
1	2	5		NA	4	4
1	NA	NA		NA	NA	NA
3	2	4		3	4	4
4	4	4		NA	4	5
5	4	4		5	4	4
5	4	4		NA	4	4
1	5	4		5	4	4
4	3	4		NA	4	4
2	4	4		NA	4	5
4	3	4		NA	3	5
4	3	3		4	4	4
3	3	3		4	4	4
4	5	5		4	4	5
2	4	4		4	4	5
2	4	4		3	4	3
4	3	4		4	3	5
2	3	4		5	4	4
4	5	1		NA	4	5
2	3	3		4	2	4
4	3	4		5	4	5
3	3	4		NA	4	4
3	5	5		3	3	4
4	3	4		2	4	4
2	3	4		5	4	5
3	3	4		NA	4	4
2	4	3		5	4	5
4	3	4		4	3	3
2	1	5		4	4	5
2	4	4		4	4	4
3	4	3		3	4	5
3	3	3		NA	4	5
NA	4	5		4	4	4
4	4	4		3	4	3
5	5	1		NA	3	NA
4	4	4		5	4	5
4	4	4		NA	5	5
4	3	4		NA	5	4
2	2	4		2	3	3
2	4	3		3	4	4
1	3	4		2	4	4
3	3	3		NA	4	4
4	3	4		5	5	4
3	4	2		4	4	4
3	4	4		NA	4	4
2	3	4		5	4	5
3	4	4		5	4	4
2	5	3		4	5	4
4	2	4		5	4	4
3	3	3		4	4	4
2	3	4		4	2	4
4	3	3		5	4	5
5	4	4		3	4	4
4	3	4		2	4	4
3	4	4		5	4	4
2	3	4		NA	4	4
3	1	3		NA	4	4
4	4	3		NA	4	3
4	3	2		NA	3	4
4	2	4		NA	5	4
5	3	5		4	4	4
4	3	4		5	3	5
4	4	5		3	4	4
4	5	2		2	4	4
3	3	4		5	4	5
2	4	4		NA	4	5
4	2	4		1	3	3
4	2	4		NA	4	5
4	2	5		5	4	4
2	3	4		NA	4	5
2	4	4		5	5	5
1	3	4		4	4	5
NA	5	4		5	4	5
4	4	1		NA	4	4
4	4	4		5	4	4
4	3	4		5	4	2
3	4	3		NA	4	4
4	3	4		4	5	5
4	5	4		NA	4	5
4	4	3		4	5	5
2	4	3		NA	4	4
4	3	4		4	4	4
4	4	5		4	5	4
1	1	3		5	4	5
4	4	4		5	4	4
2	4	3		NA	4	NA
3	4	4		NA	4	5
3	4	5		4	4	4
4	4	3		2	4	4
3	3	4		NA	4	4
4	5	4		NA	4	5
4	3	NA		NA	4	4
4	5	5		NA	4	5
4	4	4		NA	4	4
5	4	4		4	4	4
5	4	5		NA	4	4
2	4	3		NA	4	3
1	3	3		NA	4	4
3	4	3		3	3	3
3	3	4		5	4	5
1	3	4		4	4	4
4	3	4		5	4	4
4	3	4		NA	4	5
2	2	4		5	4	4
4	4	4		3	4	4
3	3	3		4	4	4
4	2	4		3	4	4
4	4	5		NA	4	4
2	4	4		4	4	4
2	3	3		NA	4	5
4	4	4		4	4	4
4	5	4		5	4	4
2	4	3		NA	4	5
2	NA	3		NA	4	4
2	4	4		NA	4	4
2	4	2		2	3	3
5	4	4		4	4	4
2	5	3		4	5	4
NA	2	4		NA	3	4
2	4	4		2	3	3
4	4	4		NA	4	4
5	5	4		4	4	5
4	4	3		NA	NA	3
4	4	2		4	4	4
3	5	5		5	5	5
3	2	3		4	5	5
1	4	4		NA	3	4
4	5	4		3	4	4
5	3	4		4	4	4
4	4	5		3	4	3
4	4	4		4	5	5
5	3	4		2	4	4
4	5	3		5	5	5
5	5	1		4	3	4
5	3	4		NA	4	4
3	2	5		NA	3	3
5	4	4		4	4	4
1	5	4		5	4	4
3	3	4		4	4	4
2	3	5		2	4	3
2	4	4		NA	4	4
NA	3	4		5	4	5
4	2	4		NA	4	3
2	3	4		NA	4	4
5	3	4		5	4	5
4	4	3		4	4	4
5	1	5		5	5	5
3	4	3		3	4	4
2	3	4		NA	4	4
4	3	4		4	NA	4
2	2	5		NA	3	4
3	3	4		4	4	4
3	3	4		NA	4	3
2	5	2		3	4	4

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298924&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [ROW]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298924&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298924&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Two Sample t-test (unpaired)
Mean of Sample 13.20121951219512
Mean of Sample 23.49700598802395
t-stat-2.56462109051312
df329
p-value0.0107721367516236
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.522670423531909,-0.0689025281257512]
F-test to compare two variances
F-stat1.34934066381656
df163
p-value0.055342043465052
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.993152746984358,1.83406956945934]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 3.20121951219512 \tabularnewline
Mean of Sample 2 & 3.49700598802395 \tabularnewline
t-stat & -2.56462109051312 \tabularnewline
df & 329 \tabularnewline
p-value & 0.0107721367516236 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.522670423531909,-0.0689025281257512] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.34934066381656 \tabularnewline
df & 163 \tabularnewline
p-value & 0.055342043465052 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.993152746984358,1.83406956945934] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298924&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]3.20121951219512[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]3.49700598802395[/C][/ROW]
[ROW][C]t-stat[/C][C]-2.56462109051312[/C][/ROW]
[ROW][C]df[/C][C]329[/C][/ROW]
[ROW][C]p-value[/C][C]0.0107721367516236[/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][-0.522670423531909,-0.0689025281257512][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.34934066381656[/C][/ROW]
[ROW][C]df[/C][C]163[/C][/ROW]
[ROW][C]p-value[/C][C]0.055342043465052[/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][0.993152746984358,1.83406956945934][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298924&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298924&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 13.20121951219512
Mean of Sample 23.49700598802395
t-stat-2.56462109051312
df329
p-value0.0107721367516236
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.522670423531909,-0.0689025281257512]
F-test to compare two variances
F-stat1.34934066381656
df163
p-value0.055342043465052
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.993152746984358,1.83406956945934]






Welch Two Sample t-test (unpaired)
Mean of Sample 13.20121951219512
Mean of Sample 23.49700598802395
t-stat-2.56115654563031
df320.107356471688
p-value0.0108904745894049
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.523000639606591,-0.068572312051069]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 3.20121951219512 \tabularnewline
Mean of Sample 2 & 3.49700598802395 \tabularnewline
t-stat & -2.56115654563031 \tabularnewline
df & 320.107356471688 \tabularnewline
p-value & 0.0108904745894049 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.523000639606591,-0.068572312051069] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298924&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]3.20121951219512[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]3.49700598802395[/C][/ROW]
[ROW][C]t-stat[/C][C]-2.56115654563031[/C][/ROW]
[ROW][C]df[/C][C]320.107356471688[/C][/ROW]
[ROW][C]p-value[/C][C]0.0108904745894049[/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][-0.523000639606591,-0.068572312051069][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298924&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298924&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 13.20121951219512
Mean of Sample 23.49700598802395
t-stat-2.56115654563031
df320.107356471688
p-value0.0108904745894049
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.523000639606591,-0.068572312051069]






Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired)
W11823
p-value0.0249501335856215
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.185446180809113
p-value0.00675158730531333
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.337994742222871
p-value1.23193643064567e-08

\begin{tabular}{lllllllll}
\hline
Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired) \tabularnewline
W & 11823 \tabularnewline
p-value & 0.0249501335856215 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.185446180809113 \tabularnewline
p-value & 0.00675158730531333 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.337994742222871 \tabularnewline
p-value & 1.23193643064567e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298924&T=3

[TABLE]
[ROW][C]Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]11823[/C][/ROW]
[ROW][C]p-value[/C][C]0.0249501335856215[/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]0.185446180809113[/C][/ROW]
[ROW][C]p-value[/C][C]0.00675158730531333[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.337994742222871[/C][/ROW]
[ROW][C]p-value[/C][C]1.23193643064567e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298924&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298924&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:

Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired)
W11823
p-value0.0249501335856215
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.185446180809113
p-value0.00675158730531333
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.337994742222871
p-value1.23193643064567e-08


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ; par2 = no ;
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):
par6 <- '0.0'
par5 <- 'unpaired'
par4 <- 'two.sided'
par3 <- '0.95'
par2 <- ''
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)
myWlabel <- 'Wilcoxon Signed-Rank Test'
if (par5=='unpaired') myWlabel = 'Wilcoxon Rank-Sum Test (Mann–Whitney U test)'
a<-table.element(a,paste(myWlabel,' 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')