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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 computationTue, 27 Oct 2009 18:57:14 -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/t1256691558ud59xptidk3p66r.htm/, Retrieved Mon, 06 May 2024 02:53:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51325, Retrieved Mon, 06 May 2024 02:53:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsrun sequence, lag
Estimated Impact141

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] [WS3 Yt-Xt] [2009-10-28 00:57:14] [a54ad7d84632b3d861404e40e79a6400] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8,50
8,60
8,50
8,20
8,10
7,90
8,60
8,70
8,70
8,50
8,40
8,50
8,70
8,70
8,60
8,50
8,30
8,00
8,20
8,10
8,10
8,00
7,90
7,90
8,00
8,00
7,90
8,00
7,70
7,20
7,50
7,30
7,00
7,00
7,00
7,20
7,30
7,10
6,80
6,40
6,10
6,50
7,70
7,90
7,50
6,90
6,60
6,90
7,70
8,00
8,00
7,70
7,30
7,40
8,10
8,30
Dataseries Y:
Download CSV
Histogram 
100,33
101,77
103
104,99
104,92
106
107,77
108,29
109,68
109,41
107,26
106,78
106,34
106,35
106,61
108,03
108,5
108,49
109,09
109,21
107,2
106,15
106,25
106,52
105,16
105,68
107,01
107,9
108,12
108,43
109,02
108,39
108,65
109,55
111,69
110,76
110,78
110,76
112,38
112,86
114,74
116,21
116,86
114,51
114,11
112,12
108,9
106,62
105,95
107,03
107,1
108
108,24
109,72
109,53
110,64

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51325&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51325&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51325&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'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c130.335680570640
b-2.80247160008219

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 130.335680570640 \tabularnewline
b & -2.80247160008219 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51325&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]130.335680570640[/C][/ROW]
[ROW][C]b[/C][C]-2.80247160008219[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51325&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51325&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]
c130.335680570640
b-2.80247160008219






Descriptive Statistics about e[t]
# observations56
minimum-6.1846719699415
Q1-1.73739073003199
median0.193968650013207
mean-2.12224830962805e-16
Q31.44347432999677
maximum8.10335074999266

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 56 \tabularnewline
minimum & -6.1846719699415 \tabularnewline
Q1 & -1.73739073003199 \tabularnewline
median & 0.193968650013207 \tabularnewline
mean & -2.12224830962805e-16 \tabularnewline
Q3 & 1.44347432999677 \tabularnewline
maximum & 8.10335074999266 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51325&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]56[/C][/ROW]
[ROW][C]minimum[/C][C]-6.1846719699415[/C][/ROW]
[ROW][C]Q1[/C][C]-1.73739073003199[/C][/ROW]
[ROW][C]median[/C][C]0.193968650013207[/C][/ROW]
[ROW][C]mean[/C][C]-2.12224830962805e-16[/C][/ROW]
[ROW][C]Q3[/C][C]1.44347432999677[/C][/ROW]
[ROW][C]maximum[/C][C]8.10335074999266[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51325&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51325&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]
# observations56
minimum-6.1846719699415
Q1-1.73739073003199
median0.193968650013207
mean-2.12224830962805e-16
Q31.44347432999677
maximum8.10335074999266


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')