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 computationWed, 17 Dec 2014 17:45:13 +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/17/t1418838381ss3r22wklmj8thu.htm/, Retrieved Fri, 17 May 2024 00:08:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270543, Retrieved Fri, 17 May 2024 00:08:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact52

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] [two sample 3] [2014-12-17 17:45:13] [a0dc8dfb1ad11084a66a61bab0a3c2c7] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12,9	9
12,2	10,5
12,8	11
7,4	11,5
6,7	10,5
12,6	13,5
14,8	10,5
13,3	12
11,1	14,5
8,2	11
11,4	10,5
6,4	11
10,6	11
12	13,5
6,3	9,5
11,3	10
11,9	12,5
9,3	11
9,6	11,5
10	9,5
6,4	10,5
13,8	17,5
10,8	10,5
13,8	11,5
11,7	11,5
10,9	11
16,1	17,5
13,4	9,5
9,9	9,5
11,5	9,5
8,3	9,5
11,7	10,5
6,1	8
9	10
9,7	16
10,8	11,5
10,3	12,5
10,4	9
12,7	12
9,3	14
11,8	11,5
5,9	10
11,4	12,5
13	11,5
10,8	9
12,3	9,5
11,3	13
11,8	10
7,9	13
12,7	8
12,3	11
11,6	10,5
6,7	9
10,9	9
12,1	9,5
13,3	12
10,1	9,5
5,7	10
14,3	10,5
8	8,5
13,3	9,5
9,3	10,5
12,5	12
7,6	9
15,9	11,5
9,2	10,5
9,1	10
11,1	14
13	10
14,5	13,5
12,2	10,5
12,3	14,5
11,4	10
8,8	9
14,6	13
7,3	12,5
12,6	10,5
13	11,5
12,6	11
13,2	10
9,9	11
7,7	10,5
10,5	10,5
13,4	9,5
10,9	10
4,3	8,5
10,3	11
11,8	11
11,2	11,5
11,4	12
8,6	10,5
13,2	9,5
12,6	8,5
5,6	9
9,9	7,5
8,8	9,5
7,7	9,5
9	8,5
7,3	9,5
11,4	9,5
13,6	9
7,9	12
10,7	9
10,3	9,5
8,3	9
9,6	10,5
14,2	9,5
8,5	11
13,5	10
4,9	8,5
6,4	8,5
9,6	9
11,6	9,5
11,1	9
4,35	5
12,7	5
18,1	20
17,85	20
16,6	15
12,6	10
17,1	20
19,1	20
16,1	20
13,35	10
18,4	20
14,7	5
10,6	15
12,6	15
16,2	20
13,6	15
18,9	20
14,1	15
14,5	15
16,15	20
14,75	15
14,8	15
12,45	10
12,65	10
17,35	15
8,6	5
18,4	20
16,1	15
11,6	10
17,75	20
15,25	20
17,65	20
15,6	20
16,35	20
17,65	20
13,6	15
11,7	20
14,35	15
14,75	20
18,25	20
9,9	20
16	15
18,25	20
16,85	20
14,6	10
13,85	10
18,95	20
15,6	15
14,85	15
11,75	10
18,45	15
15,9	10
17,1	20
16,1	5
19,9	20
10,95	5
18,45	20
15,1	15
15	15
11,35	10
15,95	15
18,1	15
14,6	20
15,4	20
15,4	20
17,6	15
13,35	15
19,1	20
15,35	20
7,6	5
13,4	10
13,9	15
19,1	20
15,25	15
12,9	20
16,1	15
17,35	15
13,15	15
12,15	15
12,6	5
10,35	5
15,4	15
9,6	10
18,2	15
13,6	10
14,85	10
14,75	20
14,1	10
14,9	10
16,25	15
19,25	20
13,6	10
13,6	20
15,65	15
12,75	20
14,6	10
9,85	5
12,65	5
11,9	5
19,2	20
16,6	15
11,2	5
15,25	20
11,9	15
13,2	10
16,35	20
12,4	15
15,85	15
14,35	20
18,15	20
11,15	5
15,65	15
17,75	20
7,65	5
12,35	15
15,6	20
19,3	20
15,2	5
17,1	20
15,6	10
18,4	15
19,05	20
18,55	20
19,1	20
13,1	10
12,85	20
9,5	10
4,5	5
11,85	5
13,6	20
11,7	10
12,4	10
13,35	15
11,4	10
14,9	15
19,9	20
17,75	20
11,2	10
14,6	15
17,6	20
14,05	15
16,1	20
13,35	20
11,85	20
11,95	10
14,75	10
15,15	10
13,2	20
16,85	15
7,85	10
7,7	10
12,6	15
7,85	15
10,95	5
12,35	10
9,95	10
14,9	15
16,65	15
13,4	10
13,95	10
15,7	15
16,85	15
10,95	5
15,35	15
12,2	10
15,1	10
17,75	15
15,2	15
14,6	15
16,65	15
8,1	5

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270543&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270543&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270543&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'Herman Ole Andreas Wold' @ wold.wessa.net






Two Sample t-test (paired)
Difference: Mean1 - Mean20.0517543859649123
t-stat0.257409650942117
df284
p-value0.797048959409846
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.343999452111999,0.447508224041824]
F-test to compare two variances
F-stat0.578010230097423
df284
p-value4.50825789999767e-06
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.45783966670133,0.729722325075913]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & 0.0517543859649123 \tabularnewline
t-stat & 0.257409650942117 \tabularnewline
df & 284 \tabularnewline
p-value & 0.797048959409846 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.343999452111999,0.447508224041824] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.578010230097423 \tabularnewline
df & 284 \tabularnewline
p-value & 4.50825789999767e-06 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.45783966670133,0.729722325075913] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270543&T=1

[TABLE]
[ROW][C]Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]0.0517543859649123[/C][/ROW]
[ROW][C]t-stat[/C][C]0.257409650942117[/C][/ROW]
[ROW][C]df[/C][C]284[/C][/ROW]
[ROW][C]p-value[/C][C]0.797048959409846[/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][-0.343999452111999,0.447508224041824][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.578010230097423[/C][/ROW]
[ROW][C]df[/C][C]284[/C][/ROW]
[ROW][C]p-value[/C][C]4.50825789999767e-06[/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][0.45783966670133,0.729722325075913][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270543&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270543&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 (paired)
Difference: Mean1 - Mean20.0517543859649123
t-stat0.257409650942117
df284
p-value0.797048959409846
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.343999452111999,0.447508224041824]
F-test to compare two variances
F-stat0.578010230097423
df284
p-value4.50825789999767e-06
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.45783966670133,0.729722325075913]






Welch Two Sample t-test (paired)
Difference: Mean1 - Mean20.0517543859649123
t-stat0.257409650942117
df284
p-value0.797048959409846
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.343999452111999,0.447508224041824]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (paired) \tabularnewline
Difference: Mean1 - Mean2 & 0.0517543859649123 \tabularnewline
t-stat & 0.257409650942117 \tabularnewline
df & 284 \tabularnewline
p-value & 0.797048959409846 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-0.343999452111999,0.447508224041824] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270543&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (paired)[/C][/ROW]
[ROW][C]Difference: Mean1 - Mean2[/C][C]0.0517543859649123[/C][/ROW]
[ROW][C]t-stat[/C][C]0.257409650942117[/C][/ROW]
[ROW][C]df[/C][C]284[/C][/ROW]
[ROW][C]p-value[/C][C]0.797048959409846[/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][-0.343999452111999,0.447508224041824][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270543&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270543&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 (paired)
Difference: Mean1 - Mean20.0517543859649123
t-stat0.257409650942117
df284
p-value0.797048959409846
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-0.343999452111999,0.447508224041824]






Wicoxon rank sum test with continuity correction (paired)
W20362
p-value0.845505303623553
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.221052631578947
p-value1.79022614354984e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.221052631578947
p-value1.79022614354984e-06

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (paired) \tabularnewline
W & 20362 \tabularnewline
p-value & 0.845505303623553 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.221052631578947 \tabularnewline
p-value & 1.79022614354984e-06 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.221052631578947 \tabularnewline
p-value & 1.79022614354984e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270543&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (paired)[/C][/ROW]
[ROW][C]W[/C][C]20362[/C][/ROW]
[ROW][C]p-value[/C][C]0.845505303623553[/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]0.221052631578947[/C][/ROW]
[ROW][C]p-value[/C][C]1.79022614354984e-06[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.221052631578947[/C][/ROW]
[ROW][C]p-value[/C][C]1.79022614354984e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270543&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270543&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 (paired)
W20362
p-value0.845505303623553
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.221052631578947
p-value1.79022614354984e-06
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.221052631578947
p-value1.79022614354984e-06


Figures (Output of Computation)

Input Parameters & R Code

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