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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 computationTue, 03 Nov 2009 13:21:59 -0700
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/Nov/03/t12572798141x7ptohf1hyz7j8.htm/, Retrieved Wed, 01 May 2024 19:24:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53390, Retrieved Wed, 01 May 2024 19:24:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [Bivariate Explora...] [2009-10-28 22:16:11] [f84db15a18b564cd160ebc7b4eade151]
-  M D    [Bivariate Explorative Data Analysis] [WS 4 Review 1.1] [2009-11-03 20:21:59] [eba9f01697e64705b70041e6f338cb22] [Current]
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Dataseries X:
2252451600
2510410816
3777946225
2886483076
1558433529
1926771025
991053361
893770816
1145280964
1530374400
1135824804
629708836
2646279364
2078812836
2758140324
2358462096
1742645025
2458672225
1072366009
1114157641
1270566025
1371517156
1273133761
439824784
3428336704
3020052025
4295491600
2659464900
2615811025
2175382881
1274775616
1105762009
1238547249
1736222224
1215568225
449864100
3150127876
2423691361
3566836729
2313898609
2253590784
2549947009
1604723481
1166154201
1358659600
2148878736
1337876929
569872384
3280540176
3179719321
3324329649
3881290000
2394047041
2618164224
1571012496
1103103369
1453668129
1874110681
936360000
482065936
Dataseries Y:
315844
314721
308025
295936
288369
294849
352836
373321
375769
373321
352836
354025
349281
346921
341056
328329
321489
323761
385641
395641
394384
374544
354025
356409
351649
348100
336400
329476
328329
328329
384400
391876
384400
345744
320356
310249
314721
301401
283024
276676
261121
249001
308025
319225
293764
277729
260100
264196
267289
258064
243049
240100
219961
228484
278784
285156
268324
256036
252004
266256




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53390&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]4 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=53390&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53390&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c345322.056187317
b-1.54463037941502e-05

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 345322.056187317 \tabularnewline
b & -1.54463037941502e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53390&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]345322.056187317[/C][/ROW]
[ROW][C]b[/C][C]-1.54463037941502e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53390&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53390&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]
c345322.056187317
b-1.54463037941502e-05







Descriptive Statistics about e[t]
# observations60
minimum-88381.8782945449
Q1-35336.4032044594
median6744.75371632064
mean1.02318153949454e-12
Q334865.9430975589
maximum68687.4926253585

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -88381.8782945449 \tabularnewline
Q1 & -35336.4032044594 \tabularnewline
median & 6744.75371632064 \tabularnewline
mean & 1.02318153949454e-12 \tabularnewline
Q3 & 34865.9430975589 \tabularnewline
maximum & 68687.4926253585 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53390&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]-88381.8782945449[/C][/ROW]
[ROW][C]Q1[/C][C]-35336.4032044594[/C][/ROW]
[ROW][C]median[/C][C]6744.75371632064[/C][/ROW]
[ROW][C]mean[/C][C]1.02318153949454e-12[/C][/ROW]
[ROW][C]Q3[/C][C]34865.9430975589[/C][/ROW]
[ROW][C]maximum[/C][C]68687.4926253585[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53390&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53390&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-88381.8782945449
Q1-35336.4032044594
median6744.75371632064
mean1.02318153949454e-12
Q334865.9430975589
maximum68687.4926253585



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')