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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_factor_analysisdm.wasp
Title produced by softwareFactor Analysis
Date of computationThu, 24 May 2012 17:47:01 -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/May/24/t1337896035rm88deam98swy3e.htm/, Retrieved Sun, 05 May 2024 13:09:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167418, Retrieved Sun, 05 May 2024 13:09:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [male,bachelor] [2012-05-24 21:47:01] [5a1a483e8dfc82db7780f9c55bb04c44] [Current]
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Dataset

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=167418&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=167418&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167418&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






Rotated Factor Loadings
VariablesFactor1Factor2
C20.6750.018
C40.740.096
C60.7540.142
C80.7110.041
C100.6090.155
C120.6190.184
C140.5110.159
C160.5390.067
C180.3190.463
C200.3140.508
C220.1160.543
C240.1910.673
C260.5660.369
C280.4480.31
C300.6060.228
C320.4820.291
C340.0760.702
C360.050.819
C380.1060.757
C400.1190.525
C420.4740.291
C440.4320.461
C460.5310.316
C480.410.385

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
C2 & 0.675 & 0.018 \tabularnewline
C4 & 0.74 & 0.096 \tabularnewline
C6 & 0.754 & 0.142 \tabularnewline
C8 & 0.711 & 0.041 \tabularnewline
C10 & 0.609 & 0.155 \tabularnewline
C12 & 0.619 & 0.184 \tabularnewline
C14 & 0.511 & 0.159 \tabularnewline
C16 & 0.539 & 0.067 \tabularnewline
C18 & 0.319 & 0.463 \tabularnewline
C20 & 0.314 & 0.508 \tabularnewline
C22 & 0.116 & 0.543 \tabularnewline
C24 & 0.191 & 0.673 \tabularnewline
C26 & 0.566 & 0.369 \tabularnewline
C28 & 0.448 & 0.31 \tabularnewline
C30 & 0.606 & 0.228 \tabularnewline
C32 & 0.482 & 0.291 \tabularnewline
C34 & 0.076 & 0.702 \tabularnewline
C36 & 0.05 & 0.819 \tabularnewline
C38 & 0.106 & 0.757 \tabularnewline
C40 & 0.119 & 0.525 \tabularnewline
C42 & 0.474 & 0.291 \tabularnewline
C44 & 0.432 & 0.461 \tabularnewline
C46 & 0.531 & 0.316 \tabularnewline
C48 & 0.41 & 0.385 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167418&T=1

[TABLE]
[ROW][C]Rotated Factor Loadings[/C][/ROW]
[ROW][C]Variables[/C][C]Factor1[/C][C]Factor2[/C][/ROW]
[ROW][C]C2[/C][C]0.675[/C][C]0.018[/C][/ROW]
[ROW][C]C4[/C][C]0.74[/C][C]0.096[/C][/ROW]
[ROW][C]C6[/C][C]0.754[/C][C]0.142[/C][/ROW]
[ROW][C]C8[/C][C]0.711[/C][C]0.041[/C][/ROW]
[ROW][C]C10[/C][C]0.609[/C][C]0.155[/C][/ROW]
[ROW][C]C12[/C][C]0.619[/C][C]0.184[/C][/ROW]
[ROW][C]C14[/C][C]0.511[/C][C]0.159[/C][/ROW]
[ROW][C]C16[/C][C]0.539[/C][C]0.067[/C][/ROW]
[ROW][C]C18[/C][C]0.319[/C][C]0.463[/C][/ROW]
[ROW][C]C20[/C][C]0.314[/C][C]0.508[/C][/ROW]
[ROW][C]C22[/C][C]0.116[/C][C]0.543[/C][/ROW]
[ROW][C]C24[/C][C]0.191[/C][C]0.673[/C][/ROW]
[ROW][C]C26[/C][C]0.566[/C][C]0.369[/C][/ROW]
[ROW][C]C28[/C][C]0.448[/C][C]0.31[/C][/ROW]
[ROW][C]C30[/C][C]0.606[/C][C]0.228[/C][/ROW]
[ROW][C]C32[/C][C]0.482[/C][C]0.291[/C][/ROW]
[ROW][C]C34[/C][C]0.076[/C][C]0.702[/C][/ROW]
[ROW][C]C36[/C][C]0.05[/C][C]0.819[/C][/ROW]
[ROW][C]C38[/C][C]0.106[/C][C]0.757[/C][/ROW]
[ROW][C]C40[/C][C]0.119[/C][C]0.525[/C][/ROW]
[ROW][C]C42[/C][C]0.474[/C][C]0.291[/C][/ROW]
[ROW][C]C44[/C][C]0.432[/C][C]0.461[/C][/ROW]
[ROW][C]C46[/C][C]0.531[/C][C]0.316[/C][/ROW]
[ROW][C]C48[/C][C]0.41[/C][C]0.385[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167418&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167418&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:

Rotated Factor Loadings
VariablesFactor1Factor2
C20.6750.018
C40.740.096
C60.7540.142
C80.7110.041
C100.6090.155
C120.6190.184
C140.5110.159
C160.5390.067
C180.3190.463
C200.3140.508
C220.1160.543
C240.1910.673
C260.5660.369
C280.4480.31
C300.6060.228
C320.4820.291
C340.0760.702
C360.050.819
C380.1060.757
C400.1190.525
C420.4740.291
C440.4320.461
C460.5310.316
C480.410.385


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = male ; par3 = bachelor ; par4 = all ; par5 = COLLES preferred ;
Parameters (R input):
par1 = 2 ; par2 = male ; par3 = bachelor ; par4 = all ; par5 = COLLES preferred ;
R code (references can be found in the software module):
library(psych)
x <- as.data.frame(read.table(file='https://automated.biganalytics.eu/download/utaut.csv',sep=',',header=T))
x$U25 <- 6-x$U25
if(par2 == 'female') x <- x[x$Gender==0,]
if(par2 == 'male') x <- x[x$Gender==1,]
if(par3 == 'prep') x <- x[x$Pop==1,]
if(par3 == 'bachelor') x <- x[x$Pop==0,]
if(par4 != 'all') {
x <- x[x$Year==as.numeric(par4),]
}
cAc <- with(x,cbind( A1, A2, A3, A4, A5, A6, A7, A8, A9,A10))
cAs <- with(x,cbind(A11,A12,A13,A14,A15,A16,A17,A18,A19,A20))
cA <- cbind(cAc,cAs)
cCa <- with(x,cbind(C1,C3,C5,C7, C9,C11,C13,C15,C17,C19,C21,C23,C25,C27,C29,C31,C33,C35,C37,C39,C41,C43,C45,C47))
cCp <- with(x,cbind(C2,C4,C6,C8,C10,C12,C14,C16,C18,C20,C22,C24,C26,C28,C30,C32,C34,C36,C38,C40,C42,C44,C46,C48))
cC <- cbind(cCa,cCp)
cU <- with(x,cbind(U1,U2,U3,U4,U5,U6,U7,U8,U9,U10,U11,U12,U13,U14,U15,U16,U17,U18,U19,U20,U21,U22,U23,U24,U25,U26,U27,U28,U29,U30,U31,U32,U33))
cE <- with(x,cbind(BC,NNZFG,MRT,AFL,LPM,LPC,W,WPA))
cX <- with(x,cbind(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18))
if (par5=='ATTLES connected') x <- cAc
if (par5=='ATTLES separate') x <- cAs
if (par5=='ATTLES all') x <- cA
if (par5=='COLLES actuals') x <- cCa
if (par5=='COLLES preferred') x <- cCp
if (par5=='COLLES all') x <- cC
if (par5=='CSUQ') x <- cU
if (par5=='Learning Activities') x <- cE
if (par5=='Exam Items') x <- cX
ncol <- length(x[1,])
for (jjj in 1:ncol) {
x <- x[!is.na(x[,jjj]),]
}
par1 <- as.numeric(par1)
nrows <- length(x[,1])
rownames(x) <- 1:nrows
y <- x
fit <- principal(y, nfactors=par1, rotate='varimax')
fit
fs <- factor.scores(y,fit)
fs
bitmap(file='test1.png')
fa.diagram(fit)
dev.off()
bitmap(file='test2.png')
plot(fs,pch=20)
text(fs,labels=rownames(y),pos=3)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Rotated Factor Loadings',par1+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variables',1,TRUE)
for (i in 1:par1) {
a<-table.element(a,paste('Factor',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (j in 1:length(fit$loadings[,1])) {
a<-table.row.start(a)
a<-table.element(a,rownames(fit$loadings)[j],header=TRUE)
for (i in 1:par1) {
a<-table.element(a,round(fit$loadings[j,i],3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')