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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_factor_analysis.wasp
Title produced by softwareFactor Analysis
Date of computationMon, 06 Nov 2023 07:28:06 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2023/Nov/06/t1699252117espmhfryjvhr9fr.htm/, Retrieved Wed, 20 May 2026 13:09:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319985, Retrieved Wed, 20 May 2026 13:09:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsOpenAI
Estimated Impact250

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [OpenAI] [2023-11-06 06:28:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
‘Q1’ 1 1 1 1 5 1 1 1 3 1 4 1 1 1 1 1 1 1 2 1 1 5 1 1 1 1 1 1 5 1 1 1 5 2 2 2 3 2 1 1 1 1 1 2 1 1 2 3 1 1
‘Q2’ 2 1 3 1 3 1 1 1 2 1 3 2 1 2 1 3 2 2 3 2 1 3 1 2 3 2 2 2 5 1 1 2 4 2 1 3 3 2 1 2 2 2 1 2 1 2 5 3 1 1
‘Q3’ 1 3 1 2 5 2 3 3 2 1 4 2 3 3 1 1 2 1 2 2 1 3 1 1 2 1 1 5 5 2 2 2 4 1 2 5 3 2 1 2 2 2 1 2 2 3 5 4 3 1
‘Q4’ 1 3 2 1 3 1 3 2 3 1 3 3 2 2 5 3 1 1 1 1 1 3 1 4 2 1 3 5 5 1 2 3 5 2 3 3 4 2 1 1 1 3 1 2 3 2 3 1 3 1
‘Q5’ 1 3 2 1 3 2 2 1 3 2 2 1 2 3 5 1 3 1 3 1 1 5 1 2 1 1 1 1 5 2 1 1 3 2 4 1 4 3 1 1 2 1 1 3 1 1 2 1 2 1
‘Q6’ 1 3 1 1 2 1 1 1 3 1 2 1 1 3 1 2 1 2 3 1 1 5 1 1 2 1 3 3 5 1 1 1 3 2 3 2 4 2 1 1 2 1 1 3 1 1 2 2 2 1
‘Q7’ 1 3 1 1 4 2 2 2 3 1 3 5 3 4 3 3 2 3 3 3 1 3 3 3 2 1 4 5 4 2 1 3 4 2 2 3 4 2 1 3 2 2 1 2 4 2 4 4 3 1
‘Q8’ 4 4 2 1 4 4 3 5 4 2 4 2 3 4 3 5 3 4 3 4 3 2 2 3 5 2 1 3 5 3 2 3 5 1 4 3 4 2 1 5 4 2 1 4 3 1 2 1 3 1
‘Q9’ 2 2 3 1 3 2 2 2 2 1 3 2 2 2 1 3 3 3 3 3 1 3 3 3 3 1 2 3 5 2 1 3 4 1 1 2 3 2 1 3 1 3 1 3 1 2 3 3 3 1
‘Q10’ 1 2 2 1 2 1 1 3 3 1 2 1 2 4 3 4 1 2 1 2 3 5 5 2 1 1 3 3 5 1 1 4 5 1 2 1 2 3 1 1 3 1 1 2 1 2 3 2 2 1

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319985&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319985&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319985&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 5 ;
Parameters (R input):
par1 = 5 ;
R code (references can be found in the software module):
par1 <- '5'
library(psych)
par1 <- as.numeric(par1)
x <- t(x)
nrows <- length(x[,1])
ncols <- length(x[1,])
y <- array(as.double(x[1:nrows,2:ncols]),dim=c(nrows,ncols-1))
colnames(y) <- colnames(x)[2:ncols]
rownames(y) <- x[,1]
print(y)
fit <- principal(y, nfactors=par1, rotate='varimax')
fit
fs <- factor.scores(y,fit)
fs
bitmap(file='test2.png')
plot(fs$scores,pch=20)
text(fs$scores,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')