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Author*The author of this computation has been verified*
R Software Modulerwasp_Bayesian_Two_Sample_Test.wasp
Title produced by softwareBayesian Two Sample Test
Date of computationTue, 01 Dec 2015 13:54:44 +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/2015/Dec/01/t1448978125lz0wjbqmitvq9lp.htm/, Retrieved Thu, 16 May 2024 13:59:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284739, Retrieved Thu, 16 May 2024 13:59:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bayesian Two Sample Test] [Bayesian test wer...] [2015-11-28 12:46:31] [2ba32e9656c7c3fdddad3ba3f1588288]
-   PD    [Bayesian Two Sample Test] [Bayesian test wer...] [2015-12-01 13:54:44] [8acc4c3875a0c63009483cc7dfb4f316] [Current]
- RM        [Multiple Regression] [Multiple regression] [2015-12-04 13:41:12] [4e6b221caf797a012ce5465db674848b]
- RM D        [] [Multiple regression] [-0001-11-30 00:00:00] [74be16979710d4c4e7c6647856088456]
- RM D        [] [Multiple regressi...] [-0001-11-30 00:00:00] [74be16979710d4c4e7c6647856088456]
- RM        [Multiple Regression] [Multiple regression] [2015-12-04 13:58:21] [4e6b221caf797a012ce5465db674848b]
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Dataseries X:
21.6 20.7
21.6 20.7
21.6 20.7
19.4 18
19.4 18
19.4 18
15.9 16.9
15.9 16.9
15.9 16.9
21.8 24.4
21.8 24.4
21.8 24.4
17.6 15.5
17.6 15.5
17.6 15.5
19 18.4
19 18.4
19 18.4
16.3 16.2
16.3 16.2
16.3 16.2
22.5 20.6
22.5 20.6
22.5 20.6
23.8 19.8
23.8 19.8
23.8 19.8
24.6 21.6
24.6 21.6
24.6 21.6
22.7 22.3
22.7 22.3
22.7 22.3
25.2 23.7
25.2 23.7
25.2 23.7
26.4 22.1
26.4 22.1
26.4 22.1
26 26.6
26 26.6
26 26.6
23.2 23.5
23.2 23.5
23.2 23.5
22.7 19.6
22.7 19.6
22.7 19.6
24 20
24 20
24 20
20.7 20.1
20.7 20.1
20.7 20.1
23.8 16
23.8 16
23.8 16
27.1 18.9
27.1 18.9
27.1 18.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time87 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 & 87 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284739&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]87 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=284739&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284739&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time87 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Bayesian Two Sample Test
> summary(r, credMass = par4, compValeff = par3)
            mean median   mode HDI%  HDIlo  HDIup compVal %>compVal
mu1       22.265 22.265 22.225   95 21.441  23.09                  
mu2       20.224 20.222 20.248   95 19.450  21.00                  
muDiff     2.042  2.043  2.086   95  0.914   3.18       0     100.0
sigma1     3.160  3.139  3.102   95  2.574   3.79                  
sigma2     2.927  2.907  2.878   95  2.378   3.51                  
sigmaDiff  0.233  0.232  0.279   95 -0.586   1.07       0      71.3
nu        46.578 38.185 23.623   95  4.632 111.01                  
log10nu    1.571  1.582  1.590   95  0.995   2.14                  
effSz      0.673  0.672  0.666   95  0.288   1.06       0     100.0

\begin{tabular}{lllllllll}
\hline
Bayesian Two Sample Test \tabularnewline
> summary(r, credMass = par4, compValeff = par3)
            mean median   mode HDI%  HDIlo  HDIup compVal %>compVal
mu1       22.265 22.265 22.225   95 21.441  23.09                  
mu2       20.224 20.222 20.248   95 19.450  21.00                  
muDiff     2.042  2.043  2.086   95  0.914   3.18       0     100.0
sigma1     3.160  3.139  3.102   95  2.574   3.79                  
sigma2     2.927  2.907  2.878   95  2.378   3.51                  
sigmaDiff  0.233  0.232  0.279   95 -0.586   1.07       0      71.3
nu        46.578 38.185 23.623   95  4.632 111.01                  
log10nu    1.571  1.582  1.590   95  0.995   2.14                  
effSz      0.673  0.672  0.666   95  0.288   1.06       0     100.0
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=284739&T=1

[TABLE]
[ROW][C]Bayesian Two Sample Test[/C][/ROW]
[ROW][C]
> summary(r, credMass = par4, compValeff = par3)
            mean median   mode HDI%  HDIlo  HDIup compVal %>compVal
mu1       22.265 22.265 22.225   95 21.441  23.09                  
mu2       20.224 20.222 20.248   95 19.450  21.00                  
muDiff     2.042  2.043  2.086   95  0.914   3.18       0     100.0
sigma1     3.160  3.139  3.102   95  2.574   3.79                  
sigma2     2.927  2.907  2.878   95  2.378   3.51                  
sigmaDiff  0.233  0.232  0.279   95 -0.586   1.07       0      71.3
nu        46.578 38.185 23.623   95  4.632 111.01                  
log10nu    1.571  1.582  1.590   95  0.995   2.14                  
effSz      0.673  0.672  0.666   95  0.288   1.06       0     100.0
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=284739&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284739&T=1

As an alternative you can also use a QR Code:  

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

Bayesian Two Sample Test
> summary(r, credMass = par4, compValeff = par3)
            mean median   mode HDI%  HDIlo  HDIup compVal %>compVal
mu1       22.265 22.265 22.225   95 21.441  23.09                  
mu2       20.224 20.222 20.248   95 19.450  21.00                  
muDiff     2.042  2.043  2.086   95  0.914   3.18       0     100.0
sigma1     3.160  3.139  3.102   95  2.574   3.79                  
sigma2     2.927  2.907  2.878   95  2.378   3.51                  
sigmaDiff  0.233  0.232  0.279   95 -0.586   1.07       0      71.3
nu        46.578 38.185 23.623   95  4.632 111.01                  
log10nu    1.571  1.582  1.590   95  0.995   2.14                  
effSz      0.673  0.672  0.666   95  0.288   1.06       0     100.0



Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0 ; par4 = 0.95 ; par5 = unpaired ; par6 = no ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ;
R code (references can be found in the software module):
library(BEST)
par1 <- as.numeric(par1) #column number of first sample
par2 <- as.numeric(par2) #column number of second sample
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
if(par6=='yes') {
par7 <- as.numeric(par7)
par8 <- as.numeric(par8)
par9 <- as.numeric(par9)
par10 <- as.numeric(par10)
par11 <- as.numeric(par11)
par12 <- as.numeric(par12)
par13 <- as.numeric(par13)
par14 <- as.numeric(par14)
par15 <- as.numeric(par15)
par16 <- as.numeric(par16)
}
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(par6=='no') {
if(par5=='unpaired') {
(r <- BESTmcmc(z[,par1],z[,par2], parallel=F))
}
if(par5=='paired') {
(r <- BESTmcmc(z[,par1]-z[,par2], parallel=F))
}
} else {
yy <- cbind(z[1,],z[2,])
if(par5=='unpaired') {
(r <- BESTmcmc(z[,par1],z[,par2], priors=list(muM = c(par7,par8), muSD = c(par9,par10), sigmaMode = c(par11,par12), sigmaSD = c(par13,par14), nuMean = par15, nuSD = par16), parallel=F))
}
if(par5=='paired') {
(r <- BESTmcmc(z[,par1]-z[,par2], priors=list(muM = c(par7,par8), muSD = c(par9,par10), sigmaMode = c(par11,par12), sigmaSD = c(par13,par14), nuMean = par15, nuSD = par16), parallel=F))
}
}
bitmap(file='test2.png')
plot(r, credMass=par4, compVal=par3)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Bayesian Two Sample Test',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('summary(r, credMass=par4, compValeff=par3)'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')