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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 computationWed, 11 Nov 2009 03:14:49 -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/11/t1257934557s5d8ve3jvrl5c12.htm/, Retrieved Fri, 29 Mar 2024 14:47:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55457, Retrieved Fri, 29 Mar 2024 14:47:07 +0000
QR Codes:

Original text written by user:Verbetering Bivariate EDA X[t] en Z[t]
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact225
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [Workshop 5 X en Z] [2009-11-04 15:35:18] [986fdfce84f082a54cc17f886bb03ad8]
-    D    [Bivariate Explorative Data Analysis] [Shw5] [2009-11-11 10:14:49] [7a39e26d7a09dd77604df90cb29f8d39] [Current]
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Dataseries X:
107.3
107.2
107.2
105.7
105.7
104.9
104.8
104
104
103.6
103.6
103.6
103.6
104.2
104.2
104.7
104.7
104.7
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.1
106.2
106.4
106.4
106.4
107
107
107
107
106.1
106.3
106.2
106.2
106.3
106.3
106.2
107.1
105.2
103.4
102.4
100.6
100.6
100.6
99.8
100.2
101.4
101
100.6
100
Dataseries Y:
82.1
55.1
60.6
56.5
53.4
58.5
60.7
47.3
53.7
46.9
51.8
55.2
61.6
47.5
46.1
54.3
49.2
62.6
54.7
48.4
42.1
46.6
55
56.7
55.7
52
65.2
51
57.3
60.5
59.2
40.8
39.5
54.6
54.7
53.3
56.7
57.8
57.1
51.1
60.3
58
63.2
54.5
50.3
48.2
51.3
52.6
68
67.5
53.4
65.3
64.9
51.9
60.6
50.5
61.5
74.4
66.4
69.8
96.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55457&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]2 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=55457&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55457&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c200.637275108391
b-1.37150127074305

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 200.637275108391 \tabularnewline
b & -1.37150127074305 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55457&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]200.637275108391[/C][/ROW]
[ROW][C]b[/C][C]-1.37150127074305[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55457&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55457&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]
c200.637275108391
b-1.37150127074305







Descriptive Statistics about e[t]
# observations61
minimum-15.6209902825534
Q1-4.68384015547908
median-0.383840155479079
mean2.25855308954226e-16
Q33.91336086111535
maximum33.312851965914

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -15.6209902825534 \tabularnewline
Q1 & -4.68384015547908 \tabularnewline
median & -0.383840155479079 \tabularnewline
mean & 2.25855308954226e-16 \tabularnewline
Q3 & 3.91336086111535 \tabularnewline
maximum & 33.312851965914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55457&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-15.6209902825534[/C][/ROW]
[ROW][C]Q1[/C][C]-4.68384015547908[/C][/ROW]
[ROW][C]median[/C][C]-0.383840155479079[/C][/ROW]
[ROW][C]mean[/C][C]2.25855308954226e-16[/C][/ROW]
[ROW][C]Q3[/C][C]3.91336086111535[/C][/ROW]
[ROW][C]maximum[/C][C]33.312851965914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55457&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55457&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]
# observations61
minimum-15.6209902825534
Q1-4.68384015547908
median-0.383840155479079
mean2.25855308954226e-16
Q33.91336086111535
maximum33.312851965914



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')