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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 computationFri, 23 Oct 2015 19:31:08 +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/2015/Oct/23/t1445625173ifsyzsf3hohd1h6.htm/, Retrieved Tue, 14 May 2024 21:55:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=282961, Retrieved Tue, 14 May 2024 21:55:04 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsF15, Ecology and Evolution, Rodentia, Pantheria, database
Estimated Impact73

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [Pantheria Data Ro...] [2015-10-23 18:31:08] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'Baiomys_taylori'	7.43	63.9	21.99	2.52	10	68.35	20.38
'Dicrostonyx_groenlandicus'	58.44	117.32	20.84	3.78	2	38.61	17.42
'Eliomys_quercinus'	114.61	138.74	22.97	4.99	1	566.36	34.8
'Lagostomus_maximus'	4660.94	523.73	155.73	1.93	1.25	287.76	55.68
'Lagurus_lagurus'	20.6	92.52	20.24	4	5.25	41.82	20.84
'Beamys_hindei' 75.8	149.23	22.79	3.49	5	181.13	38.49 1 2 3
'Chinchilla_chinchilla'	499.99	305	111	2.5	2.5	247.48	48.99
'Castor_canadensis'	18124.41	754.74	111.59	3.6	1	663.02	46.5
'Cricetomys_gambianus'	1267.52	362.64	31.45	3.11	2	177.08	34.54
'Cuniculus_paca'	8172.55	647.06	116.24	1.01	1.75	335.48	82.75
'Cynomys_gunnisoni'	797.93	279.12	29.64	4.48	1	395.29	36.65
'Cynomys_leucurus'	963.76	307.49	30.39	5.4	1	413.84	31.76
'Cynomys_ludovicianus'	797.05	294.04	33.46	4.43	1	696.9	45.57
'Dipodomys_deserti'	107.63	138.11	30.5	3.36	2.5	50.88	24.17
'Dipodomys_heermanni'	63.08	111.25	30.99	3.11	2	53.13	25.9
'Dipodomys_merriami'	37.91	98.54	30.77	2.39	1.75	67.11	20.42
'Dipodomys_microps'	56.26	112.47	30.99	2.37	1	147.92	21
'Dipodomys_spectabilis'	124.61	141.14	23.5	2.67	2	310.33	23.47
'Dolichotis_patagonum'	8000	663.84	97.97	1.75	3.5	216.03	76.28

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282961&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282961&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282961&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'George Udny Yule' @ yule.wessa.net






Rotated Factor Loadings
VariablesFactor1Factor2
AdultBodyMass_g0.91-0.044
AdultHeadBodyLength_mm0.977-0.178
GestationLength_d0.859-0.487
LitterSize-0.0490.989
LittersPerYear-0.1820.911
SexualMaturityAge_d0.6170.061
WeaningAge_d0.857-0.331

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
AdultBodyMass_g & 0.91 & -0.044 \tabularnewline
AdultHeadBodyLength_mm & 0.977 & -0.178 \tabularnewline
GestationLength_d & 0.859 & -0.487 \tabularnewline
LitterSize & -0.049 & 0.989 \tabularnewline
LittersPerYear & -0.182 & 0.911 \tabularnewline
SexualMaturityAge_d & 0.617 & 0.061 \tabularnewline
WeaningAge_d & 0.857 & -0.331 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282961&T=1

[TABLE]
[ROW][C]Rotated Factor Loadings[/C][/ROW]
[ROW][C]Variables[/C][C]Factor1[/C][C]Factor2[/C][/ROW]
[ROW][C]AdultBodyMass_g[/C][C]0.91[/C][C]-0.044[/C][/ROW]
[ROW][C]AdultHeadBodyLength_mm[/C][C]0.977[/C][C]-0.178[/C][/ROW]
[ROW][C]GestationLength_d[/C][C]0.859[/C][C]-0.487[/C][/ROW]
[ROW][C]LitterSize[/C][C]-0.049[/C][C]0.989[/C][/ROW]
[ROW][C]LittersPerYear[/C][C]-0.182[/C][C]0.911[/C][/ROW]
[ROW][C]SexualMaturityAge_d[/C][C]0.617[/C][C]0.061[/C][/ROW]
[ROW][C]WeaningAge_d[/C][C]0.857[/C][C]-0.331[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282961&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282961&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
AdultBodyMass_g0.91-0.044
AdultHeadBodyLength_mm0.977-0.178
GestationLength_d0.859-0.487
LitterSize-0.0490.989
LittersPerYear-0.1820.911
SexualMaturityAge_d0.6170.061
WeaningAge_d0.857-0.331


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ;
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='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')