Free Statistics

of Irreproducible Research!

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, 28 Oct 2009 12:40:16 -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/28/t1256755350w73qv9xs6903ydv.htm/, Retrieved Mon, 06 May 2024 05:25:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51721, Retrieved Mon, 06 May 2024 05:25:48 +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 Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Explorative Data Analysis] [cs.shw.ws4.v2.2] [2009-10-28 18:40:16] [47f146dd9fb230449e079c6cbc92f5f5] [Current]
Feedback Forum

Post a new message
Dataseries X:
0.949390007
0.954242509
0.954242509
0.954242509
0.954242509
0.954242509
0.954242509
0.954242509
0.954242509
0.954242509
0.954242509
0.959041392
0.954242509
0.954242509
0.959041392
0.954242509
0.954242509
0.954242509
0.954242509
0.949390007
0.949390007
0.949390007
0.949390007
0.944482672
0.944482672
0.939519253
0.939519253
0.929418926
0.929418926
0.924279286
0.913813852
0.913813852
0.908485019
0.908485019
0.903089987
0.897627091
0.892094603
0.886490725
0.880813592
0.875061263
0.875061263
0.875061263
0.875061263
0.875061263
0.86923172
0.86923172
0.86332286
0.86332286
0.86332286
0.857332496
0.857332496
0.86332286
0.86923172
0.86923172
0.875061263
0.880813592
0.886490725
0.897627091
0.903089987
0.913813852
Dataseries Y:
0.278753601
0.204119983
0.230448921
0.301029996
0.397940009
0.380211242
0.361727836
0.361727836
0.322219295
0.380211242
0.342422681
0.380211242
0.278753601
0.322219295
0.322219295
0.322219295
0.301029996
0.322219295
0.342422681
0.342422681
0.414973348
0.397940009
0.361727836
0.342422681
0.380211242
0.361727836
0.342422681
0.397940009
0.397940009
0.397940009
0.380211242
0.361727836
0.230448921
0.204119983
0.278753601
0.278753601
0.255272505
0.255272505
0.278753601
0.278753601
0.278753601
0.278753601
0.255272505
0.230448921
0.322219295
0.414973348
0.491361694
0.491361694
0.505149978
0.51851394
0.556302501
0.51851394
0.568201724
0.602059991
0.602059991
0.579783597
0.556302501
0.505149978
0.322219295
0.204119983




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=51721&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=51721&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51721&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]
c1.38589311166865
b-1.11451454979862

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1.38589311166865 \tabularnewline
b & -1.11451454979862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51721&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1.38589311166865[/C][/ROW]
[ROW][C]b[/C][C]-1.11451454979862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51721&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51721&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]
c1.38589311166865
b-1.11451454979862







Descriptive Statistics about e[t]
# observations60
minimum-0.180175681089996
Q1-0.0926708771594023
median0.0109731067504474
mean-1.63601590319011e-18
Q30.0643014044246279
maximum0.191435388910004

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.180175681089996 \tabularnewline
Q1 & -0.0926708771594023 \tabularnewline
median & 0.0109731067504474 \tabularnewline
mean & -1.63601590319011e-18 \tabularnewline
Q3 & 0.0643014044246279 \tabularnewline
maximum & 0.191435388910004 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51721&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]-0.180175681089996[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0926708771594023[/C][/ROW]
[ROW][C]median[/C][C]0.0109731067504474[/C][/ROW]
[ROW][C]mean[/C][C]-1.63601590319011e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0643014044246279[/C][/ROW]
[ROW][C]maximum[/C][C]0.191435388910004[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51721&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51721&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-0.180175681089996
Q1-0.0926708771594023
median0.0109731067504474
mean-1.63601590319011e-18
Q30.0643014044246279
maximum0.191435388910004



Parameters (Session):
par1 = colombia ; par2 = www.ico.org ; par3 = Prices paid to growers in exporting Member countries in US cents per lb (Arabica, 1977/1 - 2006/12) ; par4 = usa ; par5 = www.ico.org ; par6 = Retail prices in importing Member countries in US cents per lb (Arabica, 1977/1 - 2006/12) ;
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')