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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 computationFri, 11 Nov 2011 11:29:11 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/11/t132102904574qt82x565p2fxb.htm/, Retrieved Tue, 23 Jul 2024 20:51:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=141381, Retrieved Tue, 23 Jul 2024 20:51:10 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [Bivariate EDA] [2011-11-11 16:29:11] [614dd89c388120cee0dd25886939832b] [Current]
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Dataseries X:
60635408600.00
64463389370.00
66750859382.00
69032584255.95
72841303906.58
72838685607.53
75887977453.76
78936158549.66
81986612544.38
85038924238.38
87328862789.67
85794984680.72
88082838620.17
91885510657.40
96355573323.80
101321342608.80
105791395836.80
113241494103.00
117215849652.80
120940898880.60
125658810316.50
130873880200.80
139583536623.40
148226520849.00
153789461350.00
161871513310.40
171781295610.40
178996585758.20
176620960002.00
186604680395.00
187772917033.20
193109744878.60
197630528464.00
206483683756.40
203906590621.60
206783719069.34
206759082201.76
211878483671.40
214009149959.00
217203709135.40
222331811922.60
232825724880.00
241180274038.70
248494123822.10
253049202253.08
256922518700.16
254451243638.75
262662316800.94
268926171539.67
272037080259.13
281118338865.04
286389613939.39
296190694318.91
307294826961.69
309697986635.60
314369521231.48
317533640477.42
327005697520.69
332458473876.00
339794119726.27
Dataseries Y:
79717000
82855667
79346667
76270333
89532667
83541333
82456000
85818333
92106667
96873333
96580000
87769000
88396000
90995667
92785000
98112667
105779667
103660333
105435000
105204000
107466333
118554333
123614333
125620000
121524333
130830333
138871333
135215667
122096333
130005333
126566000
134808667
138761333
133778333
122598667
116446000
100745333
104419333
103477000
102054333
102446667
99528000
106549667
107587333
117091333
114029667
109721333
114697000
115063667
121234667
118393000
121308000
117579000
117414000
117740333
109417000
116442333
113311000
109391333
107198667




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141381&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141381&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141381&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Model: Y[t] = c + b X[t] + e[t]
c89495224.5619257
b0.000104467340847496

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 89495224.5619257 \tabularnewline
b & 0.000104467340847496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141381&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]89495224.5619257[/C][/ROW]
[ROW][C]b[/C][C]0.000104467340847496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141381&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141381&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]
c89495224.5619257
b0.000104467340847496







Descriptive Statistics about e[t]
# observations60
minimum-20436542.0709755
Q1-10281479.1761824
median-2692019.18408406
mean-6.67963225472098e-10
Q35261680.01693045
maximum31430573.2783183

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -20436542.0709755 \tabularnewline
Q1 & -10281479.1761824 \tabularnewline
median & -2692019.18408406 \tabularnewline
mean & -6.67963225472098e-10 \tabularnewline
Q3 & 5261680.01693045 \tabularnewline
maximum & 31430573.2783183 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141381&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]-20436542.0709755[/C][/ROW]
[ROW][C]Q1[/C][C]-10281479.1761824[/C][/ROW]
[ROW][C]median[/C][C]-2692019.18408406[/C][/ROW]
[ROW][C]mean[/C][C]-6.67963225472098e-10[/C][/ROW]
[ROW][C]Q3[/C][C]5261680.01693045[/C][/ROW]
[ROW][C]maximum[/C][C]31430573.2783183[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141381&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141381&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-20436542.0709755
Q1-10281479.1761824
median-2692019.18408406
mean-6.67963225472098e-10
Q35261680.01693045
maximum31430573.2783183



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')