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Description of Statistical Computation

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 computationThu, 05 Nov 2009 09:58:23 -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/05/t1257440379uvcc9yy7em9ksut.htm/, Retrieved Thu, 02 May 2024 17:50:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54162, Retrieved Thu, 02 May 2024 17:50:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [ws5bivarET] [2009-11-05 16:58:23] [f47dffd5f5a8c03c3681db4cc9472742] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-1,35014
-1,75014
-4,74826
-5,39779
-6,54638
-4,39779
-5,29685
-3,74826
-6,99591
-8,39497
-9,09403
-8,1445
-7,19497
-7,14544
-8,44544
-7,19685
-5,24826
-7,14638
-6,09685
-5,79685
-5,14732
-3,59873
-3,0492
-1,60061
-2,29967
-1,45014
-1,00061
-1,59967
-1,7492
-1,8492
-0,20061
0,34892
0,24892
0,79845
0,54892
-0,59967
0,14986
-0,59967
-0,30061
0,24892
-0,30061
2,09751
0,64892
3,39657
-0,00061
0,44892
1,39845
3,09751
2,64798
4,09657
0,79845
1,79751
3,09657
1,29845
3,04704
1,84798
3,19657
2,64704
2,89751
3,79751
Dataseries Y:
Download CSV
Histogram 
-0,8651
-0,9651
-3,5609
-4,18485
-5,4567
-3,68485
-4,93275
-3,9609
-7,48065
-8,92855
-9,67645
-8,3525
-7,42855
-7,0046
-8,1046
-6,83275
-4,9609
-6,7567
-5,83275
-5,83275
-5,6088
-4,33695
-3,713
-2,04115
-2,88905
-2,2651
-2,04115
-2,68905
-3,013
-3,113
-1,34115
-0,7172
-0,8172
-0,39325
-1,0172
-2,78905
-2,3651
-2,58905
-1,14115
-0,0172
-0,24115
1,85465
0,2828
2,80255
-0,54115
-0,2172
0,30675
1,25465
0,6307
2,20255
-0,29325
1,15465
2,20255
0,40675
1,9786
0,9307
2,30255
1,6786
1,35465
1,75465

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54162&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54162&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54162&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c-0.85667008796378
b0.857394104806638

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.85667008796378 \tabularnewline
b & 0.857394104806638 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54162&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.85667008796378[/C][/ROW]
[ROW][C]b[/C][C]0.857394104806638[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54162&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54162&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Model: Y[t] = c + b X[t] + e[t]
c-0.85667008796378
b0.857394104806638






Descriptive Statistics about e[t]
# observations60
minimum-1.63691899258254
Q1-0.415505007322692
median-0.0241052249884869
mean-8.72195472674068e-17
Q30.397757760552872
maximum1.39212980655006

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1.63691899258254 \tabularnewline
Q1 & -0.415505007322692 \tabularnewline
median & -0.0241052249884869 \tabularnewline
mean & -8.72195472674068e-17 \tabularnewline
Q3 & 0.397757760552872 \tabularnewline
maximum & 1.39212980655006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54162&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]-1.63691899258254[/C][/ROW]
[ROW][C]Q1[/C][C]-0.415505007322692[/C][/ROW]
[ROW][C]median[/C][C]-0.0241052249884869[/C][/ROW]
[ROW][C]mean[/C][C]-8.72195472674068e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.397757760552872[/C][/ROW]
[ROW][C]maximum[/C][C]1.39212980655006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54162&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54162&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Descriptive Statistics about e[t]
# observations60
minimum-1.63691899258254
Q1-0.415505007322692
median-0.0241052249884869
mean-8.72195472674068e-17
Q30.397757760552872
maximum1.39212980655006


Figures (Output of Computation)

Input Parameters & R Code

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')