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Author's title

Author*Unverified author*
R Software Modulerwasp_factor_analysis.wasp
Title produced by softwareFactor Analysis
Date of computationMon, 15 Jul 2019 11:31:20 +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/2019/Jul/15/t1563183106rxyxg748y1iybqm.htm/, Retrieved Wed, 12 Aug 2020 15:28:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=318847, Retrieved Wed, 12 Aug 2020 15:28:18 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact18
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [] [2019-07-15 09:31:20] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
'A.rat'	0	0.81954393554187	6.3	0.30102999566398	0.65321251377534	1.6232492903979	3	1	3
'Elephant'	3.40602894496362	3.66304097489397	2.1	0.25527250510331	1.83884909073726	2.79518458968242	3	5	4
'Baboon'	1.02325245963371	2.25406445291434	9.1	-0.15490195998574	1.43136376415899	2.25527250510331	4	4	4
'B.bat'	-1.69897000433602	-0.52287874528034	15.8	0.5910646070265	1.27875360095283	1.54406804435028	1	1	1
'Tapir'	2.20411998265592	2.22788670461367	5.2	0	1.48287358360875	2.59328606702046	4	5	4
'Cat'	0.51851393987789	1.40823996531185	10.9	0.55630250076729	1.44715803134222	1.79934054945358	1	2	1
'Chimp'	1.71733758272386	2.64345267648619	8.3	0.14612803567824	1.69897000433602	2.36172783601759	1	1	1
'Chinchilla'	-0.36653154442041	0.80617997398389	11	0.17609125905568	0.84509804001426	2.04921802267018	5	4	4
'Cow'	2.66745295288995	2.62634036737504	3.2	-0.15490195998574	1.47712125471966	2.44870631990508	5	5	5
'Mole'	-1.09691001300806	0.079181246047625	6.3	0.32221929473392	0.54406804435028	1.6232492903979	1	1	1
'Hedgehog'	-0.10237290870956	0.54406804435028	6.6	0.61278385671974	0.77815125038364	1.6232492903979	2	2	2
'Galago'	-0.69897000433602	0.69897000433602	9.5	0.079181246047625	1.01703333929878	2.07918124604762	2	2	2
'Goat'	1.44185217577329	2.06069784035361	3.3	-0.30102999566398	1.30102999566398	2.17026171539496	5	5	5
'Hamster'	-0.92081875395238	0	11	0.53147891704226	0.5910646070265	1.20411998265592	3	1	2
'Seal'	1.92941892571429	2.51188336097887	4.7	0.17609125905568	1.61278385671974	2.49136169383427	1	3	1
'Squirrel'	-1	0.60205999132796	10.4	0.53147891704226	0.95424250943932	1.44715803134222	5	1	3
'Guinea_pig'	0.01703333929878	0.74036268949424	7.4	-0.096910013008056	0.88081359228079	1.83250891270624	5	3	4
'Horse'	2.71683772329952	2.81624129999178	2.1	-0.096910013008056	1.66275783168157	2.52633927738984	5	5	5
'L.bat'	-2	-0.60205999132796	17.9	0.30102999566398	1.38021124171161	1.69897000433602	1	1	1
'Man'	1.79239168949825	3.12057393120585	6.1	0.27875360095283	2	2.42651126136458	1	1	1
'Mouse'	-1.69897000433602	-0.39794000867204	11.9	0.11394335230684	0.50514997831991	1.27875360095283	4	1	3
'N.opossum'	0.23044892137827	0.79934054945358	13.8	0.7481880270062	0.69897000433602	1.07918124604762	2	1	1
'Armadillo'	0.54406804435028	1.03342375548695	14.3	0.49136169383427	0.81291335664286	2.07918124604762	2	1	1
'O.monkey'	-0.31875876262441	1.19033169817029	15.2	0.25527250510331	1.07918124604762	2.14612803567824	2	2	2
'Patas'	1	2.06069784035361	10	-0.045757490560675	1.30535136944662	2.23044892137827	4	4	4
'Phalanger'	0.20951501454263	1.05690485133647	11.9	0.25527250510331	1.11394335230684	1.23044892137827	2	1	2
'Pig'	2.28330122870355	2.25527250510331	6.5	0.27875360095283	1.43136376415899	2.06069784035361	4	4	4
'Rabbit'	0.39794000867204	1.08278537031645	7.5	-0.045757490560675	1.25527250510331	1.49136169383427	5	5	5
'Rat'	-0.55284196865778	0.27875360095283	10.6	0.41497334797082	0.67209785793572	1.32221929473392	3	1	3
'Fox'	0.62736585659273	1.70243053644553	7.4	0.38021124171161	0.99122607569249	1.7160033436348	1	1	1
'Rhesus'	0.83250891270624	2.25285303097989	8.4	0.079181246047625	1.46239799789896	2.2148438480477	2	3	2
'G.hyrax'	-0.1249387366083	1.0899051114394	5.7	-0.045757490560675	0.84509804001426	2.35218251811136	2	2	2
'R.hyrax'	0.55630250076729	1.32221929473392	4.9	-0.30102999566398	0.77815125038364	2.35218251811136	3	2	3
'Sheep'	1.74429298312268	2.24303804868629	3.2	-0.22184874961636	1.30102999566398	2.17897694729317	5	5	5
'Tenrec'	-0.045757490560675	0.41497334797082	11	0.36172783601759	0.65321251377534	1.77815125038364	2	1	2
'T.hyrax'	0.30102999566398	1.0899051114394	4.9	-0.30102999566398	0.8750612633917	2.30102999566398	3	1	3
'Tree_shrew'	-1	0.39794000867204	13.2	0.41497334797082	0.36172783601759	1.66275783168157	3	2	2
'Vervet'	0.6222140229663	1.76342799356294	9.7	-0.22184874961636	1.38021124171161	2.32221929473392	4	3	4
'L.opossum'	0.54406804435028	0.5910646070265	12.8	0.81954393554187	0.47712125471966	1.14612803567824	2	1	1




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=318847&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=318847&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318847&T=0

As an alternative you can also use a 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







Rotated Factor Loadings
VariablesFactor1Factor2
logWb0.8820.259
logWbr0.940.2
SWS-0.635-0.477
logPS-0.396-0.685
logL0.8590.02
logtg0.8450.235
P-0.0460.958
S0.5210.739
D0.1880.964

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
logWb & 0.882 & 0.259 \tabularnewline
logWbr & 0.94 & 0.2 \tabularnewline
SWS & -0.635 & -0.477 \tabularnewline
logPS & -0.396 & -0.685 \tabularnewline
logL & 0.859 & 0.02 \tabularnewline
logtg & 0.845 & 0.235 \tabularnewline
P & -0.046 & 0.958 \tabularnewline
S & 0.521 & 0.739 \tabularnewline
D & 0.188 & 0.964 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318847&T=1

[TABLE]
[ROW][C]Rotated Factor Loadings[/C][/ROW]
[ROW][C]Variables[/C][C]Factor1[/C][C]Factor2[/C][/ROW]
[ROW][C]logWb[/C][C]0.882[/C][C]0.259[/C][/ROW]
[ROW][C]logWbr[/C][C]0.94[/C][C]0.2[/C][/ROW]
[ROW][C]SWS[/C][C]-0.635[/C][C]-0.477[/C][/ROW]
[ROW][C]logPS[/C][C]-0.396[/C][C]-0.685[/C][/ROW]
[ROW][C]logL[/C][C]0.859[/C][C]0.02[/C][/ROW]
[ROW][C]logtg[/C][C]0.845[/C][C]0.235[/C][/ROW]
[ROW][C]P[/C][C]-0.046[/C][C]0.958[/C][/ROW]
[ROW][C]S[/C][C]0.521[/C][C]0.739[/C][/ROW]
[ROW][C]D[/C][C]0.188[/C][C]0.964[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=318847&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318847&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Rotated Factor Loadings
VariablesFactor1Factor2
logWb0.8820.259
logWbr0.940.2
SWS-0.635-0.477
logPS-0.396-0.685
logL0.8590.02
logtg0.8450.235
P-0.0460.958
S0.5210.739
D0.1880.964



Parameters (Session):
par1 = 2 ;
Parameters (R input):
par1 = 2 ;
R code (references can be found in the software module):
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')