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R Software Module

rwasp_twosampletests_mean.wasp

Title produced by software

Paired and Unpaired Two Samples Tests about the Mean

Date of computation

Sat, 13 Dec 2014 14:22:58 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/13/t1418480915ht0ds88k4hrx4ae.htm/, Retrieved Thu, 16 May 2024 08:26:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267114, Retrieved Thu, 16 May 2024 08:26:13 +0000

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-       [Paired and Unpaired Two Samples Tests about the Mean] [totalsc] [2014-12-13 14:22:58] [ba449e08135e498de67ac1fe8477f1b8] [Current]

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Dataseries X:

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Histogram

Boxplots

NA 12.9
12.2 NA
NA 12.8
7.4 NA
6.7 NA
12.6 NA
NA 14.8
13.3 NA
11.1 NA
8.2 NA
11.4 NA
6.4 NA
10.6 NA
NA 12
NA 6.3
NA 11.3
11.9 NA
NA 9.3
9.6 NA
NA 10
6.4 NA
13.8 NA
NA 10.8
13.8 NA
11.7 NA
10.9 NA
16.1 NA
NA 13.4
9.9 NA
NA 11.5
NA 8.3
NA 11.7
9 NA
9.7 NA
10.8 NA
10.3 NA
NA 10.4
12.7 NA
9.3 NA
NA 11.8
5.9 NA
11.4 NA
13 NA
10.8 NA
12.3 NA
NA 11.3
11.8 NA
7.9 NA
NA 12.7
12.3 NA
11.6 NA
6.7 NA
10.9 NA
12.1 NA
13.3 NA
10.1 NA
NA 5.7
14.3 NA
NA 8
13.3 NA
9.3 NA
NA 12.5
NA 7.6
15.9 NA
NA 9.2
9.1 NA
NA 11.1
13 NA
14.5 NA
NA 12.2
NA 12.3
NA 11.4
NA 8.8
14.6 NA
NA 12.6
NA 13
12.6 NA
NA 13.2
NA 9.9
7.7 NA
NA 10.5
NA 13.4
NA 10.9
4.3 NA
NA 10.3
11.8 NA
11.2 NA
NA 11.4
NA 8.6
NA 13.2
12.6 NA
5.6 NA
9.9 NA
NA 8.8
7.7 NA
NA 9
7.3 NA
11.4 NA
13.6 NA
7.9 NA
10.7 NA
NA 10.3
8.3 NA
9.6 NA
14.2 NA
NA 8.5
NA 13.5
NA 4.9
NA 6.4
NA 9.6
NA 11.6
11.1 NA
4.35 NA
12.7 NA
18.1 NA
17.85 NA
NA 16.6
12.6 NA
17.1 NA
NA 19.1
16.1 NA
NA 13.35
NA 18.4
14.7 NA
10.6 NA
12.6 NA
16.2 NA
13.6 NA
18.9 NA
14.1 NA
14.5 NA
NA 16.15
14.75 NA
14.8 NA
12.45 NA
12.65 NA
17.35 NA
8.6 NA
NA 18.4
16.1 NA
11.6 NA
17.75 NA
15.25 NA
17.65 NA
NA 16.35
NA 17.65
13.6 NA
NA 14.35
NA 14.75
18.25 NA
NA 9.9
16 NA
18.25 NA
NA 16.85
14.6 NA
13.85 NA
18.95 NA
NA 15.6
NA 14.85
NA 11.75
NA 18.45
15.9 NA
NA 17.1
16.1 NA
NA 19.9
10.95 NA
NA 18.45
15.1 NA
NA 15
NA 11.35
15.95 NA
NA 18.1
14.6 NA
15.4 NA
15.4 NA
17.6 NA
13.35 NA
NA 19.1
15.35 NA
NA 7.6
NA 13.4
NA 13.9
19.1 NA
NA 15.25
12.9 NA
NA 16.1
NA 17.35
NA 13.15
NA 12.15
12.6 NA
10.35 NA
15.4 NA
9.6 NA
NA 18.2
NA 13.6
14.85 NA
NA 14.75
NA 14.1
NA 14.9
NA 16.25
19.25 NA
13.6 NA
NA 13.6
NA 15.65
12.75 NA
NA 14.6
9.85 NA
12.65 NA
NA 19.2
16.6 NA
11.2 NA
15.25 NA
NA 11.9
NA 13.2
NA 16.35
12.4 NA
15.85 NA
18.15 NA
11.15 NA
NA 15.65
NA 17.75
NA 7.65
12.35 NA
15.6 NA
NA 19.3
NA 15.2
NA 17.1
15.6 NA
18.4 NA
NA 19.05
NA 18.55
NA 19.1
13.1 NA
12.85 NA
9.5 NA
4.5 NA
NA 11.85
13.6 NA
11.7 NA
12.4 NA
NA 13.35
NA 11.4
14.9 NA
NA 19.9
11.2 NA
14.6 NA
NA 17.6
14.05 NA
NA 16.1
13.35 NA
11.85 NA
NA 11.95
14.75 NA
NA 15.15
13.2 NA
NA 16.85
7.85 NA
NA 7.7
NA 12.6
7.85 NA
10.95 NA
NA 12.35
9.95 NA
14.9 NA
NA 16.65
13.4 NA
NA 13.95
NA 15.7
16.85 NA
10.95 NA
NA 15.35
12.2 NA
NA 15.1
NA 17.75
15.2 NA
NA 14.6
NA 16.65

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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=267114&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=267114&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267114&T=0

As an alternative you can also use a 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 Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Two Sample t-test (unpaired)
Mean of Sample 1	12.6156050955414
Mean of Sample 2	13.4858333333333
t-stat	-2.13201983736223
df	275
p-value	0.0338914341981078
H0 value	0
Alternative	two.sided
CI Level	0.99
CI	[-1.92895188489333,0.18849540930946]
F-test to compare two variances
F-stat	0.873409687895812
df	156
p-value	0.426772659409625
H0 value	1
Alternative	two.sided
CI Level	0.99
CI	[0.555890295186893,1.35648906546386]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 12.6156050955414 \tabularnewline
Mean of Sample 2 & 13.4858333333333 \tabularnewline
t-stat & -2.13201983736223 \tabularnewline
df & 275 \tabularnewline
p-value & 0.0338914341981078 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.99 \tabularnewline
CI & [-1.92895188489333,0.18849540930946] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.873409687895812 \tabularnewline
df & 156 \tabularnewline
p-value & 0.426772659409625 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.99 \tabularnewline
CI & [0.555890295186893,1.35648906546386] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267114&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]12.6156050955414[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.4858333333333[/C][/ROW]
[ROW][C]t-stat[/C][C]-2.13201983736223[/C][/ROW]
[ROW][C]df[/C][C]275[/C][/ROW]
[ROW][C]p-value[/C][C]0.0338914341981078[/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]0.99[/C][/ROW]
[ROW][C]CI[/C][C][-1.92895188489333,0.18849540930946][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.873409687895812[/C][/ROW]
[ROW][C]df[/C][C]156[/C][/ROW]
[ROW][C]p-value[/C][C]0.426772659409625[/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]0.99[/C][/ROW]
[ROW][C]CI[/C][C][0.555890295186893,1.35648906546386][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267114&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267114&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Two Sample t-test (unpaired)
Mean of Sample 1	12.6156050955414
Mean of Sample 2	13.4858333333333
t-stat	-2.13201983736223
df	275
p-value	0.0338914341981078
H0 value	0
Alternative	two.sided
CI Level	0.99
CI	[-1.92895188489333,0.18849540930946]
F-test to compare two variances
F-stat	0.873409687895812
df	156
p-value	0.426772659409625
H0 value	1
Alternative	two.sided
CI Level	0.99
CI	[0.555890295186893,1.35648906546386]

Welch Two Sample t-test (unpaired)
Mean of Sample 1	12.6156050955414
Mean of Sample 2	13.4858333333333
t-stat	-2.11279256303995
df	246.960271424617
p-value	0.0356223085910673
H0 value	0
Alternative	two.sided
CI Level	0.99
CI	[-1.93943442619104,0.198977950607171]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 12.6156050955414 \tabularnewline
Mean of Sample 2 & 13.4858333333333 \tabularnewline
t-stat & -2.11279256303995 \tabularnewline
df & 246.960271424617 \tabularnewline
p-value & 0.0356223085910673 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.99 \tabularnewline
CI & [-1.93943442619104,0.198977950607171] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267114&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]12.6156050955414[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.4858333333333[/C][/ROW]
[ROW][C]t-stat[/C][C]-2.11279256303995[/C][/ROW]
[ROW][C]df[/C][C]246.960271424617[/C][/ROW]
[ROW][C]p-value[/C][C]0.0356223085910673[/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]0.99[/C][/ROW]
[ROW][C]CI[/C][C][-1.93943442619104,0.198977950607171][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267114&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267114&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Welch Two Sample t-test (unpaired)
Mean of Sample 1	12.6156050955414
Mean of Sample 2	13.4858333333333
t-stat	-2.11279256303995
df	246.960271424617
p-value	0.0356223085910673
H0 value	0
Alternative	two.sided
CI Level	0.99
CI	[-1.93943442619104,0.198977950607171]

Wicoxon rank sum test with continuity correction (unpaired)
W	8084.5
p-value	0.0432940367525118
H0 value	0
Alternative	two.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic	0.143683651804671
p-value	0.120586577311472
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic	0.0750530785562633
p-value	0.838213619825404

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 8084.5 \tabularnewline
p-value & 0.0432940367525118 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.143683651804671 \tabularnewline
p-value & 0.120586577311472 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0750530785562633 \tabularnewline
p-value & 0.838213619825404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267114&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]8084.5[/C][/ROW]
[ROW][C]p-value[/C][C]0.0432940367525118[/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]0.143683651804671[/C][/ROW]
[ROW][C]p-value[/C][C]0.120586577311472[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0750530785562633[/C][/ROW]
[ROW][C]p-value[/C][C]0.838213619825404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267114&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267114&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Wicoxon rank sum test with continuity correction (unpaired)
W	8084.5
p-value	0.0432940367525118
H0 value	0
Alternative	two.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic	0.143683651804671
p-value	0.120586577311472
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic	0.0750530785562633
p-value	0.838213619825404

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

Parameters (R input):

par1 = 1 ; par2 = 2 ; par3 = 0.99 ; par4 = two.sided ; par5 = unpaired ; par6 = 0 ;

R code (references can be found in the software module):

par6 <- '0'
par5 <- 'unpaired'
par4 <- 'two.sided'
par3 <- '0.95'
par2 <- '2'
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)
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code