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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 computationSun, 25 Oct 2009 05:34:14 -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/25/t1256470867rqg9xko2wo1kevu.htm/, Retrieved Mon, 29 Apr 2024 15:15:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50296, Retrieved Mon, 29 Apr 2024 15:15:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact215
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] [ws 4] [2009-10-23 17:39:06] [b5908418e3090fddbd22f5f0f774653d]
-    D      [Bivariate Explorative Data Analysis] [ws 4] [2009-10-25 11:34:14] [f7d3e79b917995ba1c8c80042fc22ef9] [Current]
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Dataseries X:
4.588024027
4.721173862
4.73532087
4.665324109
4.591071262
4.569543008
4.563305982
4.641502115
4.635699391
4.641502115
4.71939133
4.464758032
4.553876892
4.716711561
4.689511334
4.694096395
4.619073091
4.610157727
4.6121458
4.731802837
4.664382046
4.71492105
4.744062185
4.484131858
4.600157644
4.745801316
4.770684624
4.713127327
4.67562865
4.656813419
4.656813419
4.769836808
4.702296897
4.722063937
4.766438334
4.532599493
4.639571613
4.75617306
4.787491743
4.738826571
4.651099118
4.698660529
4.723841716
4.739701079
4.751000634
4.742320024
4.774068722
4.552823706
4.642465971
4.745801316
4.733563401
4.644390899
4.54648119
4.527208645
4.534747722
4.651099118
4.543294782
4.585987367
4.631812117
4.411585437
Dataseries Y:
2,2300144
2,2300144
2,163323026
2,104134154
2,116255515
2,140066163
2,151762203
2,140066163
2,104134154
2,091864062
2,066862759
2,151762203
2,163323026
2,163323026
2,140066163
2,128231706
2,140066163
2,163323026
2,163323026
2,151762203
2,140066163
2,116255515
2,079441542
2,104134154
2,091864062
2,091864062
2,079441542
2,066862759
2,066862759
2,079441542
2,079441542
2,066862759
2,079441542
2,041220329
1,974081026
2,014903021
1,987874348
1,945910149
1,945910149
1,945910149
1,974081026
1,987874348
1,960094784
1,916922612
1,85629799
1,808288771
1,871802177
2,041220329
2,066862759
2,014903021
1,931521412
1,887069649
1,931521412
2,041220329
2,079441542
2,079441542
2,041220329
1,987874348
2,00148
2,091864062




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=50296&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=50296&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50296&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'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c3.63739481288554
b-0.339149645434812

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 3.63739481288554 \tabularnewline
b & -0.339149645434812 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50296&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]3.63739481288554[/C][/ROW]
[ROW][C]b[/C][C]-0.339149645434812[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50296&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50296&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]
c3.63739481288554
b-0.339149645434812







Descriptive Statistics about e[t]
# observations60
minimum-0.220749887207534
Q1-0.0657301659444961
median0.0204343474453528
mean-2.88640593992690e-18
Q30.0625097676252155
maximum0.193804028447859

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.220749887207534 \tabularnewline
Q1 & -0.0657301659444961 \tabularnewline
median & 0.0204343474453528 \tabularnewline
mean & -2.88640593992690e-18 \tabularnewline
Q3 & 0.0625097676252155 \tabularnewline
maximum & 0.193804028447859 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50296&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]-0.220749887207534[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0657301659444961[/C][/ROW]
[ROW][C]median[/C][C]0.0204343474453528[/C][/ROW]
[ROW][C]mean[/C][C]-2.88640593992690e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0625097676252155[/C][/ROW]
[ROW][C]maximum[/C][C]0.193804028447859[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50296&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50296&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-0.220749887207534
Q1-0.0657301659444961
median0.0204343474453528
mean-2.88640593992690e-18
Q30.0625097676252155
maximum0.193804028447859



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')