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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 computationSat, 24 Oct 2009 05:21:20 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/24/t12563834724iblhip4f7bahv1.htm/, Retrieved Fri, 03 May 2024 06:34:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50075, Retrieved Fri, 03 May 2024 06:34:35 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsworkshop 4 deel 2
Estimated Impact189
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Explorative Data Analysis] [Workshop 4 ] [2009-10-24 11:21:20] [e7a989b306049c061a54f626f1127c12] [Current]
-           [Bivariate Explorative Data Analysis] [] [2009-10-27 17:29:24] [e0a128c302a1ec9189220a385b8da313]
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Dataseries X:
0.78845736
0.832909123
0.78845736
0.693147181
1.064710737
0.916290732
0.741937345
0.78845736
0.916290732
1.098612289
0.955511445
0.916290732
1.064710737
1.064710737
1.131402111
1.16315081
0.875468737
0.916290732
1.098612289
1.098612289
1.098612289
0.875468737
1.029619417
1.098612289
0.993251773
0.955511445
0.916290732
0.741937345
0.641853886
0.78845736
0.832909123
0.641853886
0.693147181
0.693147181
0.693147181
0.405465108
0.405465108
0.405465108
0.336472237
0.470003629
0.875468737
1.131402111
1.193922468
1.30833282
1.335001067
1.526056303
1.458615023
1.667706821
1.791759469
1.808288771
1.722766598
1.740466175
1.609437912
1.223775432
1.064710737
0.832909123
0.741937345
-0.223143551
-0.105360516
-0.105360516
Dataseries Y:
4.872904621
4.763881877
4.707726774
4.713127327
4.683981366
4.689511334
4.702296897
4.695924549
4.695924549
4.753590191
4.711330382
4.71939133
4.736198448
4.779963476
4.737075257
4.745801316
4.748404354
4.707726774
4.753590191
4.780802755
4.840242308
4.850466542
4.877484781
4.943782987
4.922168313
4.96284463
4.901564199
4.940927882
5.070789217
5.138148614
5.164785974
5.169346985
5.197944392
5.19462213
5.133442723
5.149237144
5.219274159
5.180096735
5.218191322
5.353752073
5.372032404
5.374815338
5.50003297
5.557985693
5.666426688
5.739471317
5.771441123
5.752890049
5.80874291
5.749711407
5.651435994
5.612763076
5.375278408
5.280153396
5.251749731
5.329816034
5.279644101
5.295814236
5.292802186
5.367843429




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50075&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50075&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50075&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c4.86305417979089
b0.255664527003886

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 4.86305417979089 \tabularnewline
b & 0.255664527003886 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50075&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]4.86305417979089[/C][/ROW]
[ROW][C]b[/C][C]0.255664527003886[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50075&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50075&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]
c4.86305417979089
b0.255664527003886







Descriptive Statistics about e[t]
# observations60
minimum-0.451281580761953
Q1-0.351658125065613
median0.0811501667210361
mean5.45489218031769e-17
Q30.273122826079254
maximum0.535470823273053

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.451281580761953 \tabularnewline
Q1 & -0.351658125065613 \tabularnewline
median & 0.0811501667210361 \tabularnewline
mean & 5.45489218031769e-17 \tabularnewline
Q3 & 0.273122826079254 \tabularnewline
maximum & 0.535470823273053 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50075&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]-0.451281580761953[/C][/ROW]
[ROW][C]Q1[/C][C]-0.351658125065613[/C][/ROW]
[ROW][C]median[/C][C]0.0811501667210361[/C][/ROW]
[ROW][C]mean[/C][C]5.45489218031769e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.273122826079254[/C][/ROW]
[ROW][C]maximum[/C][C]0.535470823273053[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50075&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50075&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]
# observations60
minimum-0.451281580761953
Q1-0.351658125065613
median0.0811501667210361
mean5.45489218031769e-17
Q30.273122826079254
maximum0.535470823273053



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
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')