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 computationSat, 06 Dec 2014 11:43:23 +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/06/t1417866482iaar6nfqgwzu6ba.htm/, Retrieved Thu, 16 May 2024 12:49:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263591, Retrieved Thu, 16 May 2024 12:49:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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] [] [2014-10-28 09:08:51] [5d70ade31d892c55b68fa1af48da4bec]
- R PD    [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-06 11:43:23] [4cfc068a520cd237806cfcade835365e] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
NA	11
NA	10
NA	7
NA	4
NA	4
NA	10
NA	4
NA	4
NA	4
NA	4
NA	10
NA	4
NA	7
NA	4
NA	14
NA	4
NA	4
NA	7
NA	10
NA	4
NA	5
NA	4
NA	4
NA	4
NA	5
NA	4
NA	6
NA	9
NA	6
NA	4
NA	11
NA	10
NA	9
NA	5
NA	4
NA	10
NA	9
NA	7
NA	9
NA	7
NA	4
NA	9
NA	4
NA	4
NA	4
NA	4
NA	4
NA	4
NA	4
NA	12
NA	17
NA	8
NA	4
NA	16
NA	19
NA	4
NA	9
NA	4
NA	5
NA	4
NA	4
NA	4
NA	5
NA	4
NA	8
NA	4
NA	4
NA	4
NA	8
NA	5
NA	6
NA	4
NA	6
NA	4
NA	4
NA	6
NA	6
NA	8
NA	9
NA	4
NA	5
NA	4
NA	9
NA	4
NA	4
NA	4
NA	4
NA	4
NA	4
NA	5
NA	4
NA	4
NA	4
NA	4
NA	4
NA	4
NA	9
NA	4
NA	9
NA	4
NA	5
NA	8
NA	4
4	NA
9	NA
5	NA
8	NA
4	NA
4	NA
4	NA
6	NA
5	NA
4	NA
7	NA
12	NA
4	NA
4	NA
4	NA
4	NA
5	NA
15	NA
10	NA
8	NA
9	NA
4	NA
4	NA
7	NA
4	NA
4	NA
4	NA
7	NA
7	NA
6	NA
4	NA
4	NA
7	NA
4	NA
4	NA
4	NA
6	NA
4	NA
5	NA
4	NA
4	NA
9	NA
4	NA
4	NA
4	NA
4	NA
4	NA
4	NA
6	NA
4	NA
5	NA
5	NA
6	NA
4	NA
4	NA
5	NA
5	NA
7	NA
5	NA
8	NA
11	NA
22	NA
4	NA
16	NA
4	NA
4	NA
4	NA
4	NA
5	NA
8	NA
7	NA
4	NA
13	NA
4	NA
4	NA
4	NA
4	NA
5	NA
12	NA
4	NA
4	NA
4	NA
4	NA
4	NA
4	NA
4	NA
5	NA
4	NA
7	NA
5	NA
4	NA
6	NA
5	NA
4	NA
8	NA
4	NA
4	NA
4	NA
4	NA
8	NA
6	NA
4	NA
4	NA
4	NA
5	NA
4	NA
4	NA
4	NA
4	NA
5	NA
4	NA
4	NA
5	NA
5	NA
NA	6
NA	7
NA	9
NA	7
NA	4
NA	4
NA	4
NA	8
NA	4
NA	4
NA	9
NA	4
NA	5
NA	6
NA	7
NA	4
NA	8
NA	11
NA	6
NA	5
NA	8
NA	9
NA	4
NA	4
NA	5
NA	5
NA	4
NA	4
NA	4
NA	17
NA	4
NA	23
NA	4
NA	5
NA	4
NA	18
NA	5
NA	4
NA	6
NA	6
NA	4
NA	15
NA	6
NA	4
NA	7
NA	4
NA	15
NA	4
NA	12
NA	5
NA	6
NA	6
NA	7
NA	7
NA	5
NA	4
NA	5
NA	4
NA	7
NA	4
NA	7
NA	4
NA	5
NA	14
NA	16
NA	10
NA	6
NA	4
NA	5
NA	4
NA	4
NA	15
NA	4
NA	8
NA	5
NA	5
NA	9
NA	9
NA	6
NA	4
NA	4
NA	4
NA	4
NA	4
NA	4
NA	4
NA	5
NA	7
NA	4
NA	5
NA	5
NA	4
NA	4
NA	6
NA	6
NA	7
NA	5
NA	5
NA	6
NA	9
NA	4
NA	4
NA	11
NA	4
NA	7
NA	9
NA	4
NA	5
NA	4
NA	4
NA	10
NA	4
NA	9
NA	14
NA	4
NA	4
NA	9
NA	7
NA	7
NA	4
NA	6
4	NA
4	NA
4	NA
9	NA
11	NA
4	NA
4	NA
6	NA
4	NA
8	NA
4	NA
4	NA
8	NA
4	NA
9	NA
4	NA
4	NA
4	NA
7	NA
5	NA
8	NA
5	NA
7	NA
4	NA
4	NA
4	NA
4	NA
7	NA
4	NA
4	NA
4	NA
12	NA
4	NA
5	NA
4	NA
5	NA
7	NA
6	NA
4	NA
6	NA
4	NA
8	NA
5	NA
4	NA
8	NA
4	NA
4	NA
5	NA
7	NA
4	NA
7	NA
11	NA
4	NA
4	NA
4	NA
4	NA
4	NA
4	NA
8	NA
4	NA
8	NA
6	NA
4	NA
10	NA
5	NA
5	NA
5	NA
4	NA
8	NA
8	NA
8	NA
4	NA
28	NA
5	NA
4	NA
5	NA
10	NA
4	NA
5	NA
8	NA
4	NA
4	NA
4	NA
6	NA
10	NA
4	NA
4	NA
14	NA
5	NA
5	NA
16	NA
7	NA
5	NA
8	NA
5	NA
4	NA
4	NA
5	NA
4	NA
5	NA
5	NA
6	NA
5	NA
7	NA
8	NA
7	NA
4	NA
6	NA
8	NA
4	NA
4	NA
7	NA
5	NA
4	NA
7	NA
13	NA
4	NA
4	NA
4	NA
4	NA
6	NA
6	NA
13	NA
4	NA
5	NA
4	NA
5	NA
4	NA
4	NA
4	NA
4	NA
12	NA
5	NA
9	NA
12	NA
16	NA
6	NA
5	NA
4	NA
9	NA
12	NA
5	NA
4	NA
6	NA
6	NA
5	NA
14	NA
4	NA
4	NA
4	NA
6	NA
4	NA
4	NA
5	NA
17	NA
4	NA
10	NA
5	NA
4	NA
5	NA

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'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263591&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263591&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263591&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 15.85401459854015
Mean of Sample 26.25892857142857
t-stat-1.40778267371248
df496
p-value0.159821840764781
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.970028245912523,0.160200300135672]
F-test to compare two variances
F-stat0.883832142594253
df273
p-value0.330847220658075
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.686691518857635,1.1339223060915]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 5.85401459854015 \tabularnewline
Mean of Sample 2 & 6.25892857142857 \tabularnewline
t-stat & -1.40778267371248 \tabularnewline
df & 496 \tabularnewline
p-value & 0.159821840764781 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.970028245912523,0.160200300135672] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.883832142594253 \tabularnewline
df & 273 \tabularnewline
p-value & 0.330847220658075 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.686691518857635,1.1339223060915] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263591&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]5.85401459854015[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]6.25892857142857[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.40778267371248[/C][/ROW]
[ROW][C]df[/C][C]496[/C][/ROW]
[ROW][C]p-value[/C][C]0.159821840764781[/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][-0.970028245912523,0.160200300135672][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.883832142594253[/C][/ROW]
[ROW][C]df[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]0.330847220658075[/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][0.686691518857635,1.1339223060915][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263591&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263591&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 15.85401459854015
Mean of Sample 26.25892857142857
t-stat-1.40778267371248
df496
p-value0.159821840764781
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.970028245912523,0.160200300135672]
F-test to compare two variances
F-stat0.883832142594253
df273
p-value0.330847220658075
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.686691518857635,1.1339223060915]






Welch Two Sample t-test (unpaired)
Mean of Sample 15.85401459854015
Mean of Sample 26.25892857142857
t-stat-1.39907585946311
df463.862071144324
p-value0.162458536316419
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.973641480143962,0.163813534367111]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 5.85401459854015 \tabularnewline
Mean of Sample 2 & 6.25892857142857 \tabularnewline
t-stat & -1.39907585946311 \tabularnewline
df & 463.862071144324 \tabularnewline
p-value & 0.162458536316419 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.973641480143962,0.163813534367111] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263591&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]5.85401459854015[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]6.25892857142857[/C][/ROW]
[ROW][C]t-stat[/C][C]-1.39907585946311[/C][/ROW]
[ROW][C]df[/C][C]463.862071144324[/C][/ROW]
[ROW][C]p-value[/C][C]0.162458536316419[/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][-0.973641480143962,0.163813534367111][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263591&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263591&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 15.85401459854015
Mean of Sample 26.25892857142857
t-stat-1.39907585946311
df463.862071144324
p-value0.162458536316419
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.973641480143962,0.163813534367111]






Wicoxon rank sum test with continuity correction (unpaired)
W28640
p-value0.173657536646377
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0849191866527633
p-value0.336495220517713
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.459821428571429
p-value0

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 28640 \tabularnewline
p-value & 0.173657536646377 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.0849191866527633 \tabularnewline
p-value & 0.336495220517713 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.459821428571429 \tabularnewline
p-value & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263591&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]28640[/C][/ROW]
[ROW][C]p-value[/C][C]0.173657536646377[/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]0.0849191866527633[/C][/ROW]
[ROW][C]p-value[/C][C]0.336495220517713[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.459821428571429[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263591&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263591&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)
W28640
p-value0.173657536646377
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0849191866527633
p-value0.336495220517713
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.459821428571429
p-value0


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 0.0 ;
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)
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')