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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 computationTue, 16 Dec 2014 10:20:18 +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/16/t1418725226t7n86oujvtfatdr.htm/, Retrieved Thu, 16 May 2024 03:35:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269253, Retrieved Thu, 16 May 2024 03:35:31 +0000
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Estimated Impact68

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Dataset

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

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'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269253&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269253&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269253&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'Gwilym Jenkins' @ jenkins.wessa.net






Two Sample t-test (unpaired)
Mean of Sample 112.725
Mean of Sample 213.0192567567568
t-stat-0.744640708457834
df294
p-value0.457083746599303
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.07196957884414,0.483456065330628]
F-test to compare two variances
F-stat0.850826183800767
df147
p-value0.328502212268992
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.615011162620037,1.17706025360098]

\begin{tabular}{lllllllll}
\hline
Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 12.725 \tabularnewline
Mean of Sample 2 & 13.0192567567568 \tabularnewline
t-stat & -0.744640708457834 \tabularnewline
df & 294 \tabularnewline
p-value & 0.457083746599303 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-1.07196957884414,0.483456065330628] \tabularnewline
F-test to compare two variances \tabularnewline
F-stat & 0.850826183800767 \tabularnewline
df & 147 \tabularnewline
p-value & 0.328502212268992 \tabularnewline
H0 value & 1 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [0.615011162620037,1.17706025360098] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269253&T=1

[TABLE]
[ROW][C]Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]12.725[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.0192567567568[/C][/ROW]
[ROW][C]t-stat[/C][C]-0.744640708457834[/C][/ROW]
[ROW][C]df[/C][C]294[/C][/ROW]
[ROW][C]p-value[/C][C]0.457083746599303[/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][-1.07196957884414,0.483456065330628][/C][/ROW]
[ROW][C]F-test to compare two variances[/C][/ROW]
[ROW][C]F-stat[/C][C]0.850826183800767[/C][/ROW]
[ROW][C]df[/C][C]147[/C][/ROW]
[ROW][C]p-value[/C][C]0.328502212268992[/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][0.615011162620037,1.17706025360098][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269253&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269253&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 112.725
Mean of Sample 213.0192567567568
t-stat-0.744640708457834
df294
p-value0.457083746599303
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.07196957884414,0.483456065330628]
F-test to compare two variances
F-stat0.850826183800767
df147
p-value0.328502212268992
H0 value1
Alternativetwo.sided
CI Level0.95
CI[0.615011162620037,1.17706025360098]






Welch Two Sample t-test (unpaired)
Mean of Sample 112.725
Mean of Sample 213.0192567567568
t-stat-0.744640708457834
df292.102467790568
p-value0.457087607820406
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.0719904611829,0.483476947669381]

\begin{tabular}{lllllllll}
\hline
Welch Two Sample t-test (unpaired) \tabularnewline
Mean of Sample 1 & 12.725 \tabularnewline
Mean of Sample 2 & 13.0192567567568 \tabularnewline
t-stat & -0.744640708457834 \tabularnewline
df & 292.102467790568 \tabularnewline
p-value & 0.457087607820406 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
CI Level & 0.95 \tabularnewline
CI & [-1.0719904611829,0.483476947669381] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269253&T=2

[TABLE]
[ROW][C]Welch Two Sample t-test (unpaired)[/C][/ROW]
[ROW][C]Mean of Sample 1[/C][C]12.725[/C][/ROW]
[ROW][C]Mean of Sample 2[/C][C]13.0192567567568[/C][/ROW]
[ROW][C]t-stat[/C][C]-0.744640708457834[/C][/ROW]
[ROW][C]df[/C][C]292.102467790568[/C][/ROW]
[ROW][C]p-value[/C][C]0.457087607820406[/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][-1.0719904611829,0.483476947669381][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269253&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269253&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 112.725
Mean of Sample 213.0192567567568
t-stat-0.744640708457834
df292.102467790568
p-value0.457087607820406
H0 value0
Alternativetwo.sided
CI Level0.95
CI[-1.0719904611829,0.483476947669381]






Wicoxon rank sum test with continuity correction (unpaired)
W10484
p-value0.525441712941944
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0878378378378378
p-value0.617731508772438
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0743243243243243
p-value0.808286885123005

\begin{tabular}{lllllllll}
\hline
Wicoxon rank sum test with continuity correction (unpaired) \tabularnewline
W & 10484 \tabularnewline
p-value & 0.525441712941944 \tabularnewline
H0 value & 0 \tabularnewline
Alternative & two.sided \tabularnewline
Kolmogorov-Smirnov Test to compare Distributions of two Samples \tabularnewline
KS Statistic & 0.0878378378378378 \tabularnewline
p-value & 0.617731508772438 \tabularnewline
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples \tabularnewline
KS Statistic & 0.0743243243243243 \tabularnewline
p-value & 0.808286885123005 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269253&T=3

[TABLE]
[ROW][C]Wicoxon rank sum test with continuity correction (unpaired)[/C][/ROW]
[ROW][C]W[/C][C]10484[/C][/ROW]
[ROW][C]p-value[/C][C]0.525441712941944[/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]0.0878378378378378[/C][/ROW]
[ROW][C]p-value[/C][C]0.617731508772438[/C][/ROW]
[ROW][C]Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples[/C][/ROW]
[ROW][C]KS Statistic[/C][C]0.0743243243243243[/C][/ROW]
[ROW][C]p-value[/C][C]0.808286885123005[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269253&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269253&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)
W10484
p-value0.525441712941944
H0 value0
Alternativetwo.sided
Kolmogorov-Smirnov Test to compare Distributions of two Samples
KS Statistic0.0878378378378378
p-value0.617731508772438
Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples
KS Statistic0.0743243243243243
p-value0.808286885123005


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')