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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 computationFri, 30 Oct 2009 16:36:58 -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/30/t1256942270h58rjzdl73iv78b.htm/, Retrieved Sun, 28 Apr 2024 19:32:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52176, Retrieved Sun, 28 Apr 2024 19:32:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
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]
-   PD  [Bivariate Data Series] [] [2009-10-30 22:08:48] [b5ba85a7ae9f50cb97d92cbc56161b32]
- RMPD      [Bivariate Explorative Data Analysis] [eda] [2009-10-30 22:36:58] [454b2df2fae01897bad5ff38ed3cc924] [Current]
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Dataseries X:
-0.597837001
-0.597837001
-0.597837001
-0.597837001
-0.597837001
-0.579818495
-0.579818495
-0.579818495
-0.579818495
-0.579818495
-0.597837001
-0.579818495
-0.597837001
-0.597837001
-0.579818495
-0.597837001
-0.597837001
-0.597837001
-0.597837001
-0.634878272
-0.634878272
-0.634878272
-0.634878272
-0.616186139
-0.616186139
-0.616186139
-0.597837001
-0.597837001
-0.616186139
-0.597837001
-0.579818495
-0.544727175
-0.527632742
-0.510825624
-0.510825624
-0.510825624
-0.527632742
-0.510825624
-0.510825624
-0.478035801
-0.430782916
-0.385662481
-0.314710745
-0.248461359
-0.248461359
-0.198450939
-0.198450939
-0.210721031
-0.186329578
-0.162518929
-0.15082289
-0.162518929
-0.162518929
-0.198450939
-0.223143551
-0.210721031
-0.223143551
-0.223143551
-0.223143551
-0.223143551
-0.235722334
Dataseries Y:
0.457424847
0.463734016
0.470003629
0.470003629
0.470003629
0.470003629
0.476234179
0.476234179
0.482426149
0.488580015
0.488580015
0.488580015
0.488580015
0.488580015
0.494696242
0.494696242
0.494696242
0.500775288
0.500775288
0.500775288
0.500775288
0.500775288
0.506817602
0.512823626
0.518793793
0.518793793
0.518793793
0.518793793
0.524728529
0.530628251
0.530628251
0.536493371
0.548121409
0.548121409
0.548121409
0.553885113
0.553885113
0.553885113
0.559615788
0.576613364
0.598836501
0.604315967
0.609765572
0.615185639
0.620576488
0.620576488
0.625938431
0.625938431
0.625938431
0.625938431
0.625938431
0.625938431
0.625938431
0.631271777
0.631271777
0.625938431
0.625938431
0.625938431
0.625938431
0.625938431
0.625938431




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=52176&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=52176&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52176&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]
c0.694557938613162
b0.31972294679292

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.694557938613162 \tabularnewline
b & 0.31972294679292 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52176&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.694557938613162[/C][/ROW]
[ROW][C]b[/C][C]0.31972294679292[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52176&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52176&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]
c0.694557938613162
b0.31972294679292







Descriptive Statistics about e[t]
# observations61
minimum-0.0459908839515995
Q1-0.0148357159515997
median0.00272460607039471
mean2.27438066387994e-18
Q30.0160972099760211
maximum0.0420097457184054

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -0.0459908839515995 \tabularnewline
Q1 & -0.0148357159515997 \tabularnewline
median & 0.00272460607039471 \tabularnewline
mean & 2.27438066387994e-18 \tabularnewline
Q3 & 0.0160972099760211 \tabularnewline
maximum & 0.0420097457184054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52176&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]-0.0459908839515995[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0148357159515997[/C][/ROW]
[ROW][C]median[/C][C]0.00272460607039471[/C][/ROW]
[ROW][C]mean[/C][C]2.27438066387994e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0160972099760211[/C][/ROW]
[ROW][C]maximum[/C][C]0.0420097457184054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52176&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52176&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-0.0459908839515995
Q1-0.0148357159515997
median0.00272460607039471
mean2.27438066387994e-18
Q30.0160972099760211
maximum0.0420097457184054



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')