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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_factor_analysis.wasp
Title produced by softwareFactor Analysis
Date of computationFri, 08 Apr 2022 06:21:03 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2022/Apr/08/t1649391787v9vn4h6drvirkmh.htm/, Retrieved Tue, 08 Sep 2026 15:54:53 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Tue, 08 Sep 2026 15:54:53 +0200
QR Codes:

Original text written by user:public information
IsPrivate?No (this computation is public)
User-defined keywordspublic information
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
अम्बेडकर नगर	398	1.85	0.00	84.41	17.16	18.68	48.81
आजमगढ़	196	1.80	0.00	82.89	31.28	18.64	49.81
बहराइच	215	0.97	0.00	71.54	10.00	16.95	45.35
बलिया	108	1.26	0.00	87.52	36.13	17.65	46.38
बलरामपुर	152	0.93	0.00	88.77	02.20	18.18	55.55
बस्ती	243	1.70	0.00	91.70	35.56	19.15	52.59
चन्दौली	157	1.50	0.21	92.71	27.92	13.59	51.39
देवरिया	159	1.77	0.00	79.34	44.89	19.48	49.78
फैजाबाद	234	2.01	0.00	69.55	09.38	18.88	48.52
गाजीपुर	160	1.75	0.00	83.66	29.30	18.35	53.24
गोंडा	322	2.13	0.11	71.33	11.90	19.62	52.00
गोरखपुर	150	1.76	0.00	92.23	23.39	16.81	49.98
जौनपुर	66	2.00	0.00	85.45	20.38	18.46	51.98
कौसाम्बी	176	1.38	0.00	64.33	00.00	16.13	52.30
कूशीनगर	261	1.72	0.00	88.32	10.17	22.17	50.59
महाराजगंज	414	1.27	0.00	89.39	39.43	19.12	48.30
मऊ	159	1.94	0.00	84.35	23.26	17.73	52.81
मिर्जापुर	266	1.90	0.00	93.46	29.28	08.80	53.38
प्रतापगढ़	143	2.04	0.00	58.49	25.69	13.38	51.50
प्रयागराज	82	2.22	0.00	81.27	00.07	12.76	49.95
संतकबीर नगर	340	1.78	0.00	85.20	05.24	18.08	48.30
संत रविदास नगर	415	2.14	0.00	86.01	09.93	13.89	51.55
सिद्धार्थनगर	97	1.30	0.00	92.50	46.70	17.51	51.03
श्रावस्ती	190	1.03	0.00	87.94	34.38	16.31	52.30
सोनभद्र	517	1.01	0.00	82.67	95.90	04.31	50.58
सुल्तानपुर	122	0.93	0.00	89.69	27.92	17.48	52.08
वाराणसी	131	2.52	0.00	83.62	45.62	16.96	53.47

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 time0 seconds
R ServerBig Analytics Cloud Computing Center


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ;
Parameters (R input):
par1 = 1 ;
R code (references can be found in the software module):
par1 <- '1'
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')