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, 26 Nov 2012 10:39:06 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/26/t1353944454m050sngv1x27v49.htm/, Retrieved Tue, 30 Apr 2024 06:59:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=193245, Retrieved Tue, 30 Apr 2024 06:59:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80

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] [WS 5 Vraag 3] [2012-10-27 11:07:29] [f8ee2fa4f3a14474001c30fec05fcd2b]
- R PD    [Paired and Unpaired Two Samples Tests about the Mean] [paper workshop 5] [2012-11-26 15:39:06] [0d2ad79739942b80a90a457d326f3d01] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26	21	21	23	17	23	4
20	16	15	24	17	20	4
19	19	18	22	18	20	6
19	18	11	20	21	21	8
20	16	8	24	20	24	8
25	23	19	27	28	22	4
25	17	4	28	19	23	4
22	12	20	27	22	20	8
26	19	16	24	16	25	5
22	16	14	23	18	23	4
17	19	10	24	25	27	4
22	20	13	27	17	27	4
19	13	14	27	14	22	4
24	20	8	28	11	24	4
26	27	23	27	27	25	4
21	17	11	23	20	22	8
13	8	9	24	22	28	4
26	25	24	28	22	28	4
20	26	5	27	21	27	4
22	13	15	25	23	25	8
14	19	5	19	17	16	4
21	15	19	24	24	28	7
7	5	6	20	14	21	4
23	16	13	28	17	24	4
17	14	11	26	23	27	5
25	24	17	23	24	14	4
25	24	17	23	24	14	4
19	9	5	20	8	27	4
20	19	9	11	22	20	4
23	19	15	24	23	21	4
22	25	17	25	25	22	4
22	19	17	23	21	21	4
21	18	20	18	24	12	15
15	15	12	20	15	20	10
20	12	7	20	22	24	4
22	21	16	24	21	19	8
18	12	7	23	25	28	4
20	15	14	25	16	23	4
28	28	24	28	28	27	4
22	25	15	26	23	22	4
18	19	15	26	21	27	7
23	20	10	23	21	26	4
20	24	14	22	26	22	6
25	26	18	24	22	21	5
26	25	12	21	21	19	4
15	12	9	20	18	24	16
17	12	9	22	12	19	5
23	15	8	20	25	26	12
21	17	18	25	17	22	6
13	14	10	20	24	28	9
18	16	17	22	15	21	9
19	11	14	23	13	23	4
22	20	16	25	26	28	5
16	11	10	23	16	10	4
24	22	19	23	24	24	4
18	20	10	22	21	21	5
20	19	14	24	20	21	4
24	17	10	25	14	24	4
14	21	4	21	25	24	4
22	23	19	12	25	25	5
24	18	9	17	20	25	4
18	17	12	20	22	23	6
21	27	16	23	20	21	4
23	25	11	23	26	16	4
17	19	18	20	18	17	18
22	22	11	28	22	25	4
24	24	24	24	24	24	6
21	20	17	24	17	23	4
22	19	18	24	24	25	4
16	11	9	24	20	23	5
21	22	19	28	19	28	4
23	22	18	25	20	26	4
22	16	12	21	15	22	5
24	20	23	25	23	19	10
24	24	22	25	26	26	5
16	16	14	18	22	18	8
16	16	14	17	20	18	8
21	22	16	26	24	25	5
26	24	23	28	26	27	4
15	16	7	21	21	12	4
25	27	10	27	25	15	4
18	11	12	22	13	21	5
23	21	12	21	20	23	4
20	20	12	25	22	22	4
17	20	17	22	23	21	8
25	27	21	23	28	24	4
24	20	16	26	22	27	5
17	12	11	19	20	22	14
19	8	14	25	6	28	8
20	21	13	21	21	26	8
15	18	9	13	20	10	4
27	24	19	24	18	19	4
22	16	13	25	23	22	6
23	18	19	26	20	21	4
16	20	13	25	24	24	7
19	20	13	25	22	25	7
25	19	13	22	21	21	4
19	17	14	21	18	20	6
19	16	12	23	21	21	4
26	26	22	25	23	24	7
21	15	11	24	23	23	4
20	22	5	21	15	18	4
24	17	18	21	21	24	8
22	23	19	25	24	24	4
20	21	14	22	23	19	4
18	19	15	20	21	20	10
18	14	12	20	21	18	8
24	17	19	23	20	20	6
24	12	15	28	11	27	4
22	24	17	23	22	23	4
23	18	8	28	27	26	4
22	20	10	24	25	23	5
20	16	12	18	18	17	4
18	20	12	20	20	21	6
25	22	20	28	24	25	4
18	12	12	21	10	23	5
16	16	12	21	27	27	7
20	17	14	25	21	24	8
19	22	6	19	21	20	5
15	12	10	18	18	27	8
19	14	18	21	15	21	10
19	23	18	22	24	24	8
16	15	7	24	22	21	5
17	17	18	15	14	15	12
28	28	9	28	28	25	4
23	20	17	26	18	25	5
25	23	22	23	26	22	4
20	13	11	26	17	24	6
17	18	15	20	19	21	4
23	23	17	22	22	22	4
16	19	15	20	18	23	7
23	23	22	23	24	22	7
11	12	9	22	15	20	10
18	16	13	24	18	23	4
24	23	20	23	26	25	5
23	13	14	22	11	23	8
21	22	14	26	26	22	11
16	18	12	23	21	25	7
24	23	20	27	23	26	4
23	20	20	23	23	22	8
18	10	8	21	15	24	6
20	17	17	26	22	24	7
9	18	9	23	26	25	5
24	15	18	21	16	20	4
25	23	22	27	20	26	8
20	17	10	19	18	21	4
21	17	13	23	22	26	8
25	22	15	25	16	21	6
22	20	18	23	19	22	4
21	20	18	22	20	16	9
21	19	12	22	19	26	5
22	18	12	25	23	28	6
27	22	20	25	24	18	4
24	20	12	28	25	25	4
24	22	16	28	21	23	4
21	18	16	20	21	21	5
18	16	18	25	23	20	6
16	16	16	19	27	25	16
22	16	13	25	23	22	6
20	16	17	22	18	21	6
18	17	13	18	16	16	4
20	18	17	20	16	18	4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193245&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]3 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=193245&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193245&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 120.641975308642
Mean of Sample 223.037037037037
t-stat-6.29546723837586
df322
p-value1.00266081886231e-09
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.14352805747272,-1.64659539931741]
F-test to compare two variances
F-stat1.32770013093389
df161
p-value0.0730529010657865
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.973768197784167,1.81027439763708]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 20.641975308642 \tabularnewline
Mean of Sample 2 & 23.037037037037 \tabularnewline
t-stat & -6.29546723837586 \tabularnewline
df & 322 \tabularnewline
p-value & 1.00266081886231e-09 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-3.14352805747272,-1.64659539931741] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 1.32770013093389 \tabularnewline
df & 161 \tabularnewline
p-value & 0.0730529010657865 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.973768197784167,1.81027439763708] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193245&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]20.641975308642[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]23.037037037037[/C][/ROW]
[ROW][C]t-stat[/C][C]-6.29546723837586[/C][/ROW]
[ROW][C]df[/C][C]322[/C][/ROW]
[ROW][C]p-value[/C][C]1.00266081886231e-09[/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][-3.14352805747272,-1.64659539931741][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]1.32770013093389[/C][/ROW]
[ROW][C]df[/C][C]161[/C][/ROW]
[ROW][C]p-value[/C][C]0.0730529010657865[/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][0.973768197784167,1.81027439763708][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193245&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193245&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 120.641975308642
Mean of Sample 223.037037037037
t-stat-6.29546723837586
df322
p-value1.00266081886231e-09
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.14352805747272,-1.64659539931741]
F-test to compare two variances
F-stat1.32770013093389
df161
p-value0.0730529010657865
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.973768197784167,1.81027439763708]






Welch Two Sample t-test (unpaired)
Mean of Sample 120.641975308642
Mean of Sample 223.037037037037
t-stat-6.29546723837586
df315.742057018695
p-value1.02468865301618e-09
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.14358402541268,-1.64653943137745]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 20.641975308642 \tabularnewline
Mean of Sample 2 & 23.037037037037 \tabularnewline
t-stat & -6.29546723837586 \tabularnewline
df & 315.742057018695 \tabularnewline
p-value & 1.02468865301618e-09 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-3.14358402541268,-1.64653943137745] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193245&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]20.641975308642[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]23.037037037037[/C][/ROW]
[ROW][C]t-stat[/C][C]-6.29546723837586[/C][/ROW]
[ROW][C]df[/C][C]315.742057018695[/C][/ROW]
[ROW][C]p-value[/C][C]1.02468865301618e-09[/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][-3.14358402541268,-1.64653943137745][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193245&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193245&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 120.641975308642
Mean of Sample 223.037037037037
t-stat-6.29546723837586
df315.742057018695
p-value1.02468865301618e-09
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-3.14358402541268,-1.64653943137745]






Wicoxon rank sum test with continuity correction (unpaired)
W8083.5
p-value1.96628459333659e-09
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.283950617283951
p-value4.2500440324833e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.123456790123457
p-value0.169213246629407

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 8083.5 \tabularnewline
p-value & 1.96628459333659e-09 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.283950617283951 \tabularnewline
p-value & 4.2500440324833e-06 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.123456790123457 \tabularnewline
p-value & 0.169213246629407 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193245&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]8083.5[/C][/ROW]
[ROW][C]p-value[/C][C]1.96628459333659e-09[/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]0.283950617283951[/C][/ROW]
[ROW][C]p-value[/C][C]4.2500440324833e-06[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.123456790123457[/C][/ROW]
[ROW][C]p-value[/C][C]0.169213246629407[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193245&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193245&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)
W8083.5
p-value1.96628459333659e-09
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.283950617283951
p-value4.2500440324833e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.123456790123457
p-value0.169213246629407


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 4 ; par3 = 0.95 ; par4 = two.sided ; par5 = unpaired ; par6 = 0.0 ;
Parameters (R input):
par1 = 1 ; par2 = 4 ; 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')