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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationWed, 24 Nov 2010 18:55:23 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/24/t12906248374st0zh1xosyj0j7.htm/, Retrieved Fri, 03 May 2024 08:53:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=100508, Retrieved Fri, 03 May 2024 08:53:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [W3_Mini_1] [2010-11-24 18:22:43] [7318566ef3ec88988be4d1362d0cf918]
- RMPD    [Bivariate Explorative Data Analysis] [W3_Mini_2] [2010-11-24 18:55:23] [edf51d809b713abfc4095a7dca74558e] [Current]
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Dataseries X:
276444
289742
303725
298305
266795
259497
266148
271037
276239
279681
277509
271115
275902
287224
300713
293860
264221
256167
262572
263276
264291
263903
260376
255603
261076
270976
285257
280445
250741
243803
253158
255542
262522
268381
267153
266424
276427
286994
303598
296806
263290
264981
272566
276475
284678
291542
291413
295916
309119
327616
Dataseries Y:
563668
586111
604378
600991
544686
537034
551531
563250
574761
580112
575093
557560
564478
580523
596594
586570
536214
523597
536535
536322
532638
528222
516141
501866
506174
517945
533590
528379
477580
469357
490243
492622
507561
516922
514258
509846
527070
541657
564591
555362
498662
511038
525919
531673
548854
560576
557274
565742
587625
619916




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100508&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100508&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100508&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c76182.563398537
b1.69166630871538

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 76182.563398537 \tabularnewline
b & 1.69166630871538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100508&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]76182.563398537[/C][/ROW]
[ROW][C]b[/C][C]1.69166630871538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100508&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100508&T=1

As an alternative you can also use a QR Code:  

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

Model: Y[t] = c + b X[t] + e[t]
c76182.563398537
b1.69166630871538







Descriptive Statistics about e[t]
# observations50
minimum-25178.0713919093
Q1-14113.3902779234
median-8853.54360252551
mean2.68975952621986e-13
Q316923.5504731691
maximum31274.2271482348

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 50 \tabularnewline
minimum & -25178.0713919093 \tabularnewline
Q1 & -14113.3902779234 \tabularnewline
median & -8853.54360252551 \tabularnewline
mean & 2.68975952621986e-13 \tabularnewline
Q3 & 16923.5504731691 \tabularnewline
maximum & 31274.2271482348 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100508&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]50[/C][/ROW]
[ROW][C]minimum[/C][C]-25178.0713919093[/C][/ROW]
[ROW][C]Q1[/C][C]-14113.3902779234[/C][/ROW]
[ROW][C]median[/C][C]-8853.54360252551[/C][/ROW]
[ROW][C]mean[/C][C]2.68975952621986e-13[/C][/ROW]
[ROW][C]Q3[/C][C]16923.5504731691[/C][/ROW]
[ROW][C]maximum[/C][C]31274.2271482348[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100508&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100508&T=2

As an alternative you can also use a QR Code:  

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

Descriptive Statistics about e[t]
# observations50
minimum-25178.0713919093
Q1-14113.3902779234
median-8853.54360252551
mean2.68975952621986e-13
Q316923.5504731691
maximum31274.2271482348



Parameters (Session):
par1 = 0 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t] bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')