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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 computationThu, 06 Sep 2018 14:27:52 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Sep/06/t153623691978jvvbbk3g1ta5o.htm/, Retrieved Thu, 02 May 2024 08:28:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=315465, Retrieved Thu, 02 May 2024 08:28:08 +0000
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User-defined keywords
Estimated Impact60

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10 10 10 10 21 36 1 0
8 8 9 15 22 32 1 1
8 6 12 14 17 33 1 1
9 10 14 14 21 39 1 1
5 8 6 8 19 34 1 0
10 10 13 19 23 39 1 1
8 7 12 17 21 36 1 1
9 10 13 18 22 33 1 1
8 6 6 10 11 30 1 0
7 7 12 15 20 39 1 0
10 9 10 16 18 37 1 0
10 6 9 12 16 37 1 0
9 7 12 13 18 35 1 1
4 6 7 10 13 32 1 0
4 4 10 14 17 36 1 1
8 6 11 15 20 36 1 1
9 8 15 20 20 41 1 1
10 9 10 9 15 36 1 1
8 8 12 12 18 37 1 0
5 6 10 13 15 29 1 0
10 6 12 16 19 39 1 1
8 10 11 12 19 37 1 0
7 8 11 14 19 32 1 1
8 8 12 15 20 36 1 1
8 7 15 19 20 43 1 1
9 4 12 16 16 30 1 0
8 9 11 16 18 33 1 0
6 8 9 14 17 28 1 1
8 10 11 14 18 30 1 1
8 8 11 14 13 28 1 0
5 6 9 13 20 39 0 1
9 7 15 18 21 34 1 1
8 8 12 15 17 34 1 0
8 5 9 15 19 29 1 0
8 10 12 15 20 32 1 0
6 2 12 13 15 33 1 0
6 6 9 14 15 27 1 0
9 7 9 15 19 35 1 1
8 5 11 14 18 38 1 1
9 8 12 19 22 40 1 1
10 7 12 16 20 34 1 1
8 7 12 16 18 34 0 0
8 10 12 12 14 26 1 0
7 7 6 10 15 39 1 0
7 6 11 11 17 34 1 1
10 10 12 13 16 39 1 1
8 6 9 14 17 26 1 1
7 5 11 11 15 30 1 1
10 8 9 11 17 34 1 1
7 8 10 16 18 34 1 1
7 5 10 9 16 29 1 0
9 8 9 16 18 41 1 0
9 10 12 19 22 43 1 0
8 7 11 13 16 31 1 0
6 7 9 15 16 33 1 0
8 7 9 14 20 34 1 0
9 7 12 15 18 30 1 1
2 2 6 11 16 23 0 0
6 4 10 14 16 29 1 0
8 6 12 15 20 35 1 1
8 7 11 17 21 40 0 1
7 9 14 16 18 27 0 0
8 9 8 13 15 30 1 0
6 4 9 15 18 27 1 0
10 9 10 14 18 29 1 0
10 9 10 15 20 33 1 0
10 8 10 14 18 32 1 0
8 7 11 12 16 33 1 0
8 9 10 12 19 36 1 1
7 7 12 15 20 34 1 1
10 6 14 17 22 45 1 1
5 7 10 13 18 30 0 0
3 2 8 5 8 22 0 1
2 3 8 7 13 24 0 1
3 4 7 10 13 25 0 1
4 5 11 15 18 26 0 1
2 2 6 9 12 27 0 0
6 6 9 9 16 27 0 0
8 8 12 15 21 35 1 0
8 5 12 14 20 36 1 0
5 4 12 11 18 32 0 0
10 10 9 18 22 35 1 1
9 10 15 20 23 35 1 1
8 10 15 20 23 36 1 1
9 9 13 16 21 37 1 1
8 5 9 15 16 33 1 1
5 5 12 14 14 25 1 0
7 7 9 13 18 35 1 1
9 10 15 18 22 37 1 1
8 9 11 14 20 36 1 0
4 8 11 12 18 35 1 1
7 8 6 9 12 29 1 1
8 8 14 19 17 35 1 1
7 8 11 13 15 31 1 0
7 8 8 12 18 30 1 1
9 7 10 14 18 37 1 0
6 6 10 6 15 36 1 1
7 8 9 14 16 35 1 0
4 2 8 11 15 32 1 0
6 5 9 11 16 34 1 1
10 4 10 14 19 37 1 0
9 9 11 12 19 36 1 1
10 10 14 19 23 39 1 1
8 6 12 13 20 37 1 0
4 4 9 14 18 31 0 0
8 10 13 17 21 40 1 1
5 6 8 12 19 38 1 0
8 7 12 16 18 35 0 1
9 7 14 15 19 38 0 1
8 8 9 15 17 32 1 0
4 6 10 15 21 41 1 1
8 5 12 16 19 28 1 0
10 6 12 15 24 40 1 1
6 7 9 12 12 25 1 0
7 6 9 13 15 28 1 0
10 9 12 14 18 37 1 1
9 9 15 17 19 37 1 1
8 7 12 14 22 40 1 1
3 6 11 14 19 26 0 0
8 7 8 14 16 30 1 0
7 7 11 15 19 32 1 0
7 8 11 11 18 31 1 0
8 7 10 11 18 28 1 0
8 8 12 16 19 34 1 1
7 7 9 12 21 39 1 0
7 4 11 12 19 33 0 1
9 10 15 19 22 43 1 0
9 8 14 18 23 37 0 1
9 8 6 16 17 31 1 0
4 2 9 16 18 31 0 1
6 6 9 13 19 34 1 0
6 4 8 11 15 32 1 1
6 4 7 10 14 27 0 0
8 9 10 14 18 34 1 0
3 2 6 14 17 28 0 0
8 6 9 14 19 32 0 0
8 7 9 16 16 39 0 1
6 4 7 10 14 28 0 1
10 10 11 16 20 39 1 0
2 3 9 7 16 32 0 0
9 7 12 16 18 36 0 1
6 4 9 15 16 31 0 1
6 8 10 17 21 39 0 0
5 4 11 11 16 23 0 0
4 5 7 11 14 25 0 0
7 6 12 10 16 32 1 0
5 5 8 13 19 32 0 1
8 9 13 14 19 36 0 1
6 6 11 13 19 39 0 0
9 8 11 13 18 31 0 1
6 4 12 12 16 32 1 0
4 4 11 10 14 28 0 1
7 8 12 15 19 34 0 0
2 4 3 6 11 28 0 1
8 10 10 15 18 38 1 1
9 8 13 15 18 35 1 1
6 5 10 11 16 32 1 0
5 3 6 14 20 26 0 1
7 7 11 14 18 32 0 1
8 6 12 16 20 28 1 1
4 5 9 12 16 31 1 0
9 5 10 15 18 33 0 1
9 9 15 20 19 38 1 0
9 2 9 12 19 38 0 1
7 7 6 9 15 36 0 0
5 7 9 13 17 31 1 1
7 5 15 15 21 36 0 0
9 9 15 19 24 43 1 1
8 4 9 11 16 37 1 1
6 5 11 11 13 28 0 1
9 9 9 17 21 35 0 1
8 7 11 15 16 34 1 1
7 6 10 14 17 40 1 1
7 8 9 15 17 31 1 0
7 7 6 11 18 41 0 0
8 6 12 12 18 35 1 0
10 8 13 15 23 38 1 1
6 6 12 16 20 37 0 0
6 7 12 16 20 31 0 0

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315465&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]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=315465&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315465&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 time2 seconds
R ServerBig Analytics Cloud Computing Center






Two Sample t-test (unpaired)
Mean of Sample 17.27932960893855
Mean of Sample 26.75418994413408
t-stat2.45555176595327
df356
p-value0.0145441899665627
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.104555609687886,0.945723719921053]
F-test to compare two variances
F-stat0.889584329406992
df178
p-value0.435875688581987
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.66248649665755,1.1945304291018]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 7.27932960893855 \tabularnewline
Mean of Sample 2 & 6.75418994413408 \tabularnewline
t-stat & 2.45555176595327 \tabularnewline
df & 356 \tabularnewline
p-value & 0.0145441899665627 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.104555609687886,0.945723719921053] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.889584329406992 \tabularnewline
df & 178 \tabularnewline
p-value & 0.435875688581987 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.66248649665755,1.1945304291018] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315465&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]7.27932960893855[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]6.75418994413408[/C][/ROW]
[ROW][C]t-stat[/C][C]2.45555176595327[/C][/ROW]
[ROW][C]df[/C][C]356[/C][/ROW]
[ROW][C]p-value[/C][C]0.0145441899665627[/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][0.104555609687886,0.945723719921053][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.889584329406992[/C][/ROW]
[ROW][C]df[/C][C]178[/C][/ROW]
[ROW][C]p-value[/C][C]0.435875688581987[/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][0.66248649665755,1.1945304291018][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315465&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315465&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 17.27932960893855
Mean of Sample 26.75418994413408
t-stat2.45555176595327
df356
p-value0.0145441899665627
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.104555609687886,0.945723719921053]
F-test to compare two variances
F-stat0.889584329406992
df178
p-value0.435875688581987
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.66248649665755,1.1945304291018]






Welch Two Sample t-test (unpaired)
Mean of Sample 17.27932960893855
Mean of Sample 26.75418994413408
t-stat2.45555176595327
df354.788569535167
p-value0.0145458297422354
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.104550711017878,0.945728618591061]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 7.27932960893855 \tabularnewline
Mean of Sample 2 & 6.75418994413408 \tabularnewline
t-stat & 2.45555176595327 \tabularnewline
df & 354.788569535167 \tabularnewline
p-value & 0.0145458297422354 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.104550711017878,0.945728618591061] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315465&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]7.27932960893855[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]6.75418994413408[/C][/ROW]
[ROW][C]t-stat[/C][C]2.45555176595327[/C][/ROW]
[ROW][C]df[/C][C]354.788569535167[/C][/ROW]
[ROW][C]p-value[/C][C]0.0145458297422354[/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][0.104550711017878,0.945728618591061][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315465&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315465&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 17.27932960893855
Mean of Sample 26.75418994413408
t-stat2.45555176595327
df354.788569535167
p-value0.0145458297422354
H0 value0
Alternativetwo.sided
CI Level0.95
CI[0.104550711017878,0.945728618591061]






Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired)
W18588
p-value0.00793284141251193
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.167597765363129
p-value0.0131046773662116
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.167597765363129
p-value0.0131046773662116

\begin{tabular}{lllllllll}
\hline
Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired) \tabularnewline
W & 18588 \tabularnewline
p-value & 0.00793284141251193 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.167597765363129 \tabularnewline
p-value & 0.0131046773662116 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.167597765363129 \tabularnewline
p-value & 0.0131046773662116 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315465&T=3

[TABLE]
[ROW][C]Wilcoxon Rank-Sum Test (Mann–Whitney U test) with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]18588[/C][/ROW]
[ROW][C]p-value[/C][C]0.00793284141251193[/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]0.167597765363129[/C][/ROW]
[ROW][C]p-value[/C][C]0.0131046773662116[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.167597765363129[/C][/ROW]
[ROW][C]p-value[/C][C]0.0131046773662116[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315465&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315465&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)
W18588
p-value0.00793284141251193
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.167597765363129
p-value0.0131046773662116
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.167597765363129
p-value0.0131046773662116


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = 0 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
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)
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')