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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 computationWed, 28 Oct 2009 16:49:59 -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/t1256770232i54ajg9ojzz1x4m.htm/, Retrieved Sun, 05 May 2024 20:58:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51897, Retrieved Sun, 05 May 2024 20:58:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

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] [ws 5 3 Y Kl] [2009-10-28 22:40:39] [6e4e01d7eb22a9f33d58ebb35753a195]
-    D  [Bivariate Explorative Data Analysis] [ws 5 3 Y Pr] [2009-10-28 22:43:22] [6e4e01d7eb22a9f33d58ebb35753a195]
-    D      [Bivariate Explorative Data Analysis] [ws 5 et et'] [2009-10-28 22:49:59] [2e4ef2c1b76db9b31c0a03b96e94ad77] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
30,35
28,22
22,72
17,50
16,03
12,83
10,23
7,85
-1,94
-9,49
-10,51
-10,51
-9,41
-8,67
-10,63
-12,18
-13,05
-10,85
-10,05
-12,26
-17,32
-19,77
-18,01
-17,84
-13,94
-10,23
-10,16
-11,46
-10,17
-11,07
-10,87
-9,87
-16,10
-10,97
-9,23
-7,18
0,52
7,45
6,85
5,83
1,57
1,91
5,31
5,59
1,47
0,03
2,76
1,50
11,92
15,45
19,05
14,11
6,24
5,19
6,09
10,04
11,53
8,98
11,10
17,50
Dataseries Y:
Download CSV
Histogram 
0,05
0,05
-0,03
-0,07
0,02
0,05
0,05
0,04
-0,20
-0,27
-0,30
-0,29
-0,29
-0,26
-0,25
-0,22
-0,18
-0,18
-0,18
-0,19
-0,26
-0,04
0,03
0,06
0,06
0,07
0,12
0,29
0,30
0,28
0,28
0,28
0,14
0,31
0,46
0,46
0,46
0,50
0,45
0,34
0,29
0,28
0,28
0,29
0,17
0,07
0,03
0,06
0,08
0,18
0,01
-0,15
-0,29
-0,27
-0,27
-0,32
-0,41
-0,66
-0,63
-0,67

Tables (Output of Computation)





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=51897&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=51897&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51897&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c0.000165983392506
b-0.00204982248204731

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.000165983392506 \tabularnewline
b & -0.00204982248204731 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51897&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.000165983392506[/C][/ROW]
[ROW][C]b[/C][C]-0.00204982248204731[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51897&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51897&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]
c0.000165983392506
b-0.00204982248204731






Descriptive Statistics about e[t]
# observations60
minimum-0.641758577503721
Q1-0.248270257037091
median0.0488737337533226
mean-6.61363325216158e-18
Q30.257244972855333
maximum0.515105194098746

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.641758577503721 \tabularnewline
Q1 & -0.248270257037091 \tabularnewline
median & 0.0488737337533226 \tabularnewline
mean & -6.61363325216158e-18 \tabularnewline
Q3 & 0.257244972855333 \tabularnewline
maximum & 0.515105194098746 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51897&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]-0.641758577503721[/C][/ROW]
[ROW][C]Q1[/C][C]-0.248270257037091[/C][/ROW]
[ROW][C]median[/C][C]0.0488737337533226[/C][/ROW]
[ROW][C]mean[/C][C]-6.61363325216158e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.257244972855333[/C][/ROW]
[ROW][C]maximum[/C][C]0.515105194098746[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51897&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51897&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-0.641758577503721
Q1-0.248270257037091
median0.0488737337533226
mean-6.61363325216158e-18
Q30.257244972855333
maximum0.515105194098746


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')