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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hierarchicalclusteringdm.wasp
Title produced by softwareHierarchical Clustering
Date of computationTue, 28 Aug 2012 10:14:10 -0400
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/Aug/28/t1346163299j0dyp0i6daj31jj.htm/, Retrieved Fri, 03 May 2024 14:11:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169524, Retrieved Fri, 03 May 2024 14:11:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [] [2012-05-01 12:45:50] [0cacbd6f25ea662f229a505efea21410]
- RM    [Hierarchical Clustering] [] [2012-05-01 16:25:01] [0cacbd6f25ea662f229a505efea21410]
- R P     [Hierarchical Clustering] [] [2012-05-21 14:20:14] [0cacbd6f25ea662f229a505efea21410]
- R P         [Hierarchical Clustering] [variabelen] [2012-08-28 14:14:10] [8690b0a5633f6ac5ed8a33b8894b072f] [Current]
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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=169524&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=169524&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169524&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Summary of Dendrogram
LabelHeight
C118.7616630392937
C320.0755827544896
C521.095023109729
C721.3307290077015
C921.4941852602047
C1121.9808225263465
C1322.0680764907139
C1522.0907220343745
C1722.4722050542442
C1922.6495033058122
C2122.781571499789
C2322.781571499789
C2523.0217288664427
C2723.3452350598575
C2923.473389188611
C3123.7276210354093
C3323.9582971014219
C3524.3233771291461
C3724.4335834457412
C3925.0791300465423
C4125.5530063245417
C4325.7433971582875
C4527.2029410174709
C4727.568565397082
C227.6405499221705
C428.0464579805063
C628.2311884269862
C828.2842712474619
C1029.7828803759201
C1229.9375159325236
C1432.4737498593185
C1632.891372118781
C1833.0510023668279
C2035.1314247933075
C2235.6181730370839
C2435.7239206995587
C2636.261364056632
C2836.9632976264245
C3038.570983959731
C3239.0082570741321
C3446.6000286891364
C3651.7457419120095
C3855.4846208136102
C4057.9256433695349
C4259.3614002046824
C4468.3051027372943
C46118.285791890572

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
C1 & 18.7616630392937 \tabularnewline
C3 & 20.0755827544896 \tabularnewline
C5 & 21.095023109729 \tabularnewline
C7 & 21.3307290077015 \tabularnewline
C9 & 21.4941852602047 \tabularnewline
C11 & 21.9808225263465 \tabularnewline
C13 & 22.0680764907139 \tabularnewline
C15 & 22.0907220343745 \tabularnewline
C17 & 22.4722050542442 \tabularnewline
C19 & 22.6495033058122 \tabularnewline
C21 & 22.781571499789 \tabularnewline
C23 & 22.781571499789 \tabularnewline
C25 & 23.0217288664427 \tabularnewline
C27 & 23.3452350598575 \tabularnewline
C29 & 23.473389188611 \tabularnewline
C31 & 23.7276210354093 \tabularnewline
C33 & 23.9582971014219 \tabularnewline
C35 & 24.3233771291461 \tabularnewline
C37 & 24.4335834457412 \tabularnewline
C39 & 25.0791300465423 \tabularnewline
C41 & 25.5530063245417 \tabularnewline
C43 & 25.7433971582875 \tabularnewline
C45 & 27.2029410174709 \tabularnewline
C47 & 27.568565397082 \tabularnewline
C2 & 27.6405499221705 \tabularnewline
C4 & 28.0464579805063 \tabularnewline
C6 & 28.2311884269862 \tabularnewline
C8 & 28.2842712474619 \tabularnewline
C10 & 29.7828803759201 \tabularnewline
C12 & 29.9375159325236 \tabularnewline
C14 & 32.4737498593185 \tabularnewline
C16 & 32.891372118781 \tabularnewline
C18 & 33.0510023668279 \tabularnewline
C20 & 35.1314247933075 \tabularnewline
C22 & 35.6181730370839 \tabularnewline
C24 & 35.7239206995587 \tabularnewline
C26 & 36.261364056632 \tabularnewline
C28 & 36.9632976264245 \tabularnewline
C30 & 38.570983959731 \tabularnewline
C32 & 39.0082570741321 \tabularnewline
C34 & 46.6000286891364 \tabularnewline
C36 & 51.7457419120095 \tabularnewline
C38 & 55.4846208136102 \tabularnewline
C40 & 57.9256433695349 \tabularnewline
C42 & 59.3614002046824 \tabularnewline
C44 & 68.3051027372943 \tabularnewline
C46 & 118.285791890572 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169524&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]C1[/C][C]18.7616630392937[/C][/ROW]
[ROW][C]C3[/C][C]20.0755827544896[/C][/ROW]
[ROW][C]C5[/C][C]21.095023109729[/C][/ROW]
[ROW][C]C7[/C][C]21.3307290077015[/C][/ROW]
[ROW][C]C9[/C][C]21.4941852602047[/C][/ROW]
[ROW][C]C11[/C][C]21.9808225263465[/C][/ROW]
[ROW][C]C13[/C][C]22.0680764907139[/C][/ROW]
[ROW][C]C15[/C][C]22.0907220343745[/C][/ROW]
[ROW][C]C17[/C][C]22.4722050542442[/C][/ROW]
[ROW][C]C19[/C][C]22.6495033058122[/C][/ROW]
[ROW][C]C21[/C][C]22.781571499789[/C][/ROW]
[ROW][C]C23[/C][C]22.781571499789[/C][/ROW]
[ROW][C]C25[/C][C]23.0217288664427[/C][/ROW]
[ROW][C]C27[/C][C]23.3452350598575[/C][/ROW]
[ROW][C]C29[/C][C]23.473389188611[/C][/ROW]
[ROW][C]C31[/C][C]23.7276210354093[/C][/ROW]
[ROW][C]C33[/C][C]23.9582971014219[/C][/ROW]
[ROW][C]C35[/C][C]24.3233771291461[/C][/ROW]
[ROW][C]C37[/C][C]24.4335834457412[/C][/ROW]
[ROW][C]C39[/C][C]25.0791300465423[/C][/ROW]
[ROW][C]C41[/C][C]25.5530063245417[/C][/ROW]
[ROW][C]C43[/C][C]25.7433971582875[/C][/ROW]
[ROW][C]C45[/C][C]27.2029410174709[/C][/ROW]
[ROW][C]C47[/C][C]27.568565397082[/C][/ROW]
[ROW][C]C2[/C][C]27.6405499221705[/C][/ROW]
[ROW][C]C4[/C][C]28.0464579805063[/C][/ROW]
[ROW][C]C6[/C][C]28.2311884269862[/C][/ROW]
[ROW][C]C8[/C][C]28.2842712474619[/C][/ROW]
[ROW][C]C10[/C][C]29.7828803759201[/C][/ROW]
[ROW][C]C12[/C][C]29.9375159325236[/C][/ROW]
[ROW][C]C14[/C][C]32.4737498593185[/C][/ROW]
[ROW][C]C16[/C][C]32.891372118781[/C][/ROW]
[ROW][C]C18[/C][C]33.0510023668279[/C][/ROW]
[ROW][C]C20[/C][C]35.1314247933075[/C][/ROW]
[ROW][C]C22[/C][C]35.6181730370839[/C][/ROW]
[ROW][C]C24[/C][C]35.7239206995587[/C][/ROW]
[ROW][C]C26[/C][C]36.261364056632[/C][/ROW]
[ROW][C]C28[/C][C]36.9632976264245[/C][/ROW]
[ROW][C]C30[/C][C]38.570983959731[/C][/ROW]
[ROW][C]C32[/C][C]39.0082570741321[/C][/ROW]
[ROW][C]C34[/C][C]46.6000286891364[/C][/ROW]
[ROW][C]C36[/C][C]51.7457419120095[/C][/ROW]
[ROW][C]C38[/C][C]55.4846208136102[/C][/ROW]
[ROW][C]C40[/C][C]57.9256433695349[/C][/ROW]
[ROW][C]C42[/C][C]59.3614002046824[/C][/ROW]
[ROW][C]C44[/C][C]68.3051027372943[/C][/ROW]
[ROW][C]C46[/C][C]118.285791890572[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169524&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169524&T=1

As an alternative you can also use a QR Code:  

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

Summary of Dendrogram
LabelHeight
C118.7616630392937
C320.0755827544896
C521.095023109729
C721.3307290077015
C921.4941852602047
C1121.9808225263465
C1322.0680764907139
C1522.0907220343745
C1722.4722050542442
C1922.6495033058122
C2122.781571499789
C2322.781571499789
C2523.0217288664427
C2723.3452350598575
C2923.473389188611
C3123.7276210354093
C3323.9582971014219
C3524.3233771291461
C3724.4335834457412
C3925.0791300465423
C4125.5530063245417
C4325.7433971582875
C4527.2029410174709
C4727.568565397082
C227.6405499221705
C428.0464579805063
C628.2311884269862
C828.2842712474619
C1029.7828803759201
C1229.9375159325236
C1432.4737498593185
C1632.891372118781
C1833.0510023668279
C2035.1314247933075
C2235.6181730370839
C2435.7239206995587
C2636.261364056632
C2836.9632976264245
C3038.570983959731
C3239.0082570741321
C3446.6000286891364
C3651.7457419120095
C3855.4846208136102
C4057.9256433695349
C4259.3614002046824
C4468.3051027372943
C46118.285791890572



Parameters (Session):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ; par5 = all ; par6 = bachelor ; par7 = all ; par8 = COLLES all ; par9 = cases ;
Parameters (R input):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ; par5 = all ; par6 = all ; par7 = all ; par8 = COLLES all ; par9 = variables ;
R code (references can be found in the software module):
par9 <- 'cases'
par8 <- 'COLLES all'
par7 <- 'all'
par6 <- 'all'
par5 <- 'all'
par4 <- 'FALSE'
par3 <- 'FALSE'
par2 <- 'ALL'
par1 <- 'ward'
x <- as.data.frame(read.table(file='https://automated.biganalytics.eu/download/utaut.csv',sep=',',header=T))
x$U25 <- 6-x$U25
if(par5 == 'female') x <- x[x$Gender==0,]
if(par5 == 'male') x <- x[x$Gender==1,]
if(par6 == 'prep') x <- x[x$Pop==1,]
if(par6 == 'bachelor') x <- x[x$Pop==0,]
if(par7 != 'all') {
x <- x[x$Year==as.numeric(par7),]
}
cAc <- with(x,cbind( A1, A2, A3, A4, A5, A6, A7, A8, A9,A10))
cAs <- with(x,cbind(A11,A12,A13,A14,A15,A16,A17,A18,A19,A20))
cA <- cbind(cAc,cAs)
cCa <- with(x,cbind(C1,C3,C5,C7, C9,C11,C13,C15,C17,C19,C21,C23,C25,C27,C29,C31,C33,C35,C37,C39,C41,C43,C45,C47))
cCp <- with(x,cbind(C2,C4,C6,C8,C10,C12,C14,C16,C18,C20,C22,C24,C26,C28,C30,C32,C34,C36,C38,C40,C42,C44,C46,C48))
cC <- cbind(cCa,cCp)
cU <- with(x,cbind(U1,U2,U3,U4,U5,U6,U7,U8,U9,U10,U11,U12,U13,U14,U15,U16,U17,U18,U19,U20,U21,U22,U23,U24,U25,U26,U27,U28,U29,U30,U31,U32,U33))
cE <- with(x,cbind(BC,NNZFG,MRT,AFL,LPM,LPC,W,WPA))
cX <- with(x,cbind(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18))
if (par8=='ATTLES connected') x <- cAc
if (par8=='ATTLES separate') x <- cAs
if (par8=='ATTLES all') x <- cA
if (par8=='COLLES actuals') x <- cCa
if (par8=='COLLES preferred') x <- cCp
if (par8=='COLLES all') x <- cC
if (par8=='CSUQ') x <- cU
if (par8=='Learning Activities') x <- cE
if (par8=='Exam Items') x <- cX
ncol <- length(x[1,])
for (jjj in 1:ncol) {
x <- x[!is.na(x[,jjj]),]
}
par3 <- as.logical(par3)
par4 <- as.logical(par4)
if (par3 == TRUE){
dum = xlab
xlab = ylab
ylab = dum
}
if (par9=='variables') {
x <- t(x)
} else {
ncol <- length(x[1,])
colnames(x) <- 1:ncol
}
hc <- hclust(dist(x),method=par1)
d <- as.dendrogram(hc)
str(d)
mysub <- paste('Method: ',par1)
bitmap(file='test1.png')
if (par4 == TRUE){
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
if (par2 != 'ALL'){
if (par3 == TRUE){
ylab = 'cluster'
} else {
xlab = 'cluster'
}
par2 <- as.numeric(par2)
memb <- cutree(hc, k = par2)
cent <- NULL
for(k in 1:par2){
cent <- rbind(cent, colMeans(x[memb == k, , drop = FALSE]))
}
hc1 <- hclust(dist(cent),method=par1, members = table(memb))
de <- as.dendrogram(hc1)
bitmap(file='test2.png')
if (par4 == TRUE){
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
str(de)
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- length(x[,1])-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,hc$labels[i])
a<-table.element(a,hc$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
if (par2 != 'ALL'){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Cut Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- par2-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,i)
a<-table.element(a,hc1$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}