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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, 24 Feb 2014 01:36:23 -0500
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/Feb/24/t1393223907f94liisdqt6832i.htm/, Retrieved Thu, 16 May 2024 14:21:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=233991, Retrieved Thu, 16 May 2024 14:21:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [Rotated Factor Lo...] [2014-02-24 06:36:23] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
x <- array(list('Environmental legislation' 4 4 5 5 5 4 4 4 4 5 5 4 1 4 4 4 4 5 4 3 5 4 3 5 4 5 5 5 4 3 4 3 2 4 5 3 4 2 4 4 4 5 4 4 4 1
'Planning policies' 3 5 4 5 5 4 3 5 4 5 5 4 1 4 4 4 4 2 4 4 4 4 4 4 3 4 5 5 4 2 3 4 5 3 4 4 5 4 4 4 4 5 4 4 4 4
'Corporate Social Responsibilities' 5 5 2 5 2 3 4 4 5 3 4 5 1 4 4 4 4 3 5 3 4 3 2 4 3 3 4 5 5 4 5 1 5 5 4 5 1 4 2 3 4 2 4 4 4 3
'Partnership with local councils'	4 4 3 2 2 3 3 2 3 3 4 4 1 4 4 4 4 2 5 3 4 3 3 3 3 4 3 3 2 5 5 5 4 1 4 5 5 2 1 5 2 4 5 5 5 5	
'Business risk of future legislation' 4 3 3 3 2 3 4 2 3 3 4 4 2 4 4 4 4 1 5 4 4 4 3 3 3 3 3 5 5 4 5 4 5 4 5 5 4 5 4 2 4 4 4 4 1 1
'Marketing benefits' 3 1 2 3 2 4 4 2 3 2 4 4 2 4 4 4 3 1 5 3 4 3 4 3 3 2 4 5 4 4 5 1 4 5 4 2 5 4 1 5 4 5 4 5 5 4
'Customer demand'	3 2 1 3 5 3 3 2 4 2 4 4 2 4 4 4 3 3 4 5 4 4 4 3 3 4 4 5 4 4 5 4 5 4 4 5 4 5 4 5 5 4 5 5 5 4
'Eco-town opportunities' 3 3 4 3 5 3 5 2 4 2 4 4 2 4 3 4 3 2 4 3 4 3 4 4 3 4 4 5 5 4 3 4 5 5 3 5 4 5 5 4 4 4 4 5 5 5
'Potential sales price premiums'	3 2 3 3 1 4 4 2 4 2 4 4 2 4 5 4 3 4 5 3 3 2 4 4 2 2 4 5 4 4 5 1 4 5 3 4 5 4 5 3 4 4 5 5 4 5
'Fiscal incentives (i.e. Tax reliefs. subsidy)' 5 4 3 4 1 4 3 2 5 5 4 5 2 4 5 4 4 5 4 5 4 5 5 4 2 4 5 5 4 3 5 3 4 5 1 4 5 5 2 3 4 5 4 5 4 4
'Government grants (i.e. Extra funding)' 4 4 3 4 1 5 4 5 5 5 4 5 2 4 5 4 4 4 4 5 4 5 5 3 2 4 5 5 4 4 5 5 1 4 2 5 4 4 5 5 4 5 5 5 5 5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233991&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233991&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233991&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 5 ;
Parameters (R input):
par1 = 2 ;
R code (references can be found in the software module):
par1 <- '2'
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]
y
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$scores,pch=20)
text(fs$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')