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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, 28 Oct 2009 12:25:11 -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/t1256754386okwtohuchhvmbyz.htm/, Retrieved Sun, 05 May 2024 23:08:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51700, Retrieved Sun, 05 May 2024 23:08:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsEDA Bivariate Log berekening
Estimated Impact109
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 - Part2: Biv...] [2009-10-28 17:55:28] [b00a5c3d5f6ccb867aa9e2de58adfa61]
- RMP     [Kendall tau Rank Correlation] [WS 4 - Part2: Ken...] [2009-10-28 18:16:14] [b00a5c3d5f6ccb867aa9e2de58adfa61]
- RMPD        [Bivariate Explorative Data Analysis] [WS 4 - Part2: Log...] [2009-10-28 18:25:11] [63d6214c2814604a6f6cfa44dba5912e] [Current]
- RMP           [Pearson Correlation] [WS 4 - Part2: Log...] [2009-10-28 18:29:07] [b00a5c3d5f6ccb867aa9e2de58adfa61]
- RMP             [Kendall tau Rank Correlation] [WS 4 - Part2: Log...] [2009-10-28 18:32:10] [b00a5c3d5f6ccb867aa9e2de58adfa61]
- RMPD            [Bivariate Explorative Data Analysis] [WS 4 - Part2: Biv...] [2009-10-28 18:40:34] [b00a5c3d5f6ccb867aa9e2de58adfa61]
- RMP               [Pearson Correlation] [WS 4 - Part2: Pea...] [2009-10-28 18:55:17] [b00a5c3d5f6ccb867aa9e2de58adfa61]
- RMP               [Kendall tau Rank Correlation] [WS 4 - Part2: Ken...] [2009-10-28 18:58:53] [b00a5c3d5f6ccb867aa9e2de58adfa61]
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Dataseries X:
1.037
1.000
0.963787827345555
0.963787827345555
0.977723605288848
0.982271233039568
0.977723605288848
0.959041392321094
0.949390006644913
0.954242509439325
1.004
1.012
1.008
0.982271233039568
0.963787827345555
0.968482948553935
0.973127853599699
0.973127853599699
0.963787827345555
0.954242509439325
0.954242509439325
0.954242509439325
0.991226075692495
1.0
0.991226075692495
0.968482948553935
0.954242509439325
0.954242509439325
0.959041392321094
0.959041392321094
0.959041392321094
0.963787827345555
0.944482672150169
0.919078092376074
0.924279286061882
0.90848501887865
0.886490725172482
0.897627091290441
0.897627091290441
0.903089986991944
0.897627091290441
0.880813592280791
0.851258348719075
0.832508912706236
0.812913356642856
0.838849090737255
0.913813852383717
0.939519252618618
0.919078092376074
0.897627091290441
0.8750612633917
0.89209460269048
0.919078092376074
0.924279286061882
0.913813852383717
0.886490725172482
0.857332496431269
0.863322860120456
0.90848501887865
0.929418925714293
Dataseries Y:
0.90848501887865	
0.886490725172482	
0.8750612633917	
0.880813592280791	
0.89209460269048	
0.89209460269048	
0.89209460269048	
0.8750612633917	
0.8750612633917	
0.851258348719075	
0.8750612633917	
0.8750612633917	
0.880813592280791	
0.886490725172482	
0.886490725172482	
0.897627091290441	
0.90848501887865	
0.913813852383717	
0.913813852383717	
0.913813852383717	
0.897627091290441	
0.863322860120456	
0.838849090737255	
0.819543935541869	
0.826074802700826	
0.838849090737255	
0.845098040014257	
0.851258348719075	
0.857332496431269	
0.851258348719075	
0.838849090737255	
0.845098040014257	
0.832508912706236	
0.806179973983887	
0.826074802700826	
0.819543935541869	
0.806179973983887	
0.799340549453582	
0.792391689498254	
0.812913356642856	
0.832508912706236	
0.832508912706236	
0.806179973983887	
0.785329835010767	
0.763427993562937	
0.785329835010767	
0.857332496431269	
0.863322860120456	
0.838849090737255	
0.785329835010767	
0.763427993562937	
0.792391689498254	
0.851258348719075	
0.886490725172482	
0.897627091290441	
0.886490725172482	
0.869231719730976	
0.8750612633917	
0.903089986991944	
0.90848501887865	




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=51700&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=51700&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51700&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'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c0.380683668144721
b0.505076495298722

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.380683668144721 \tabularnewline
b & 0.505076495298722 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51700&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.380683668144721[/C][/ROW]
[ROW][C]b[/C][C]0.505076495298722[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51700&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51700&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]
c0.380683668144721
b0.505076495298722







Descriptive Statistics about e[t]
# observations60
minimum-0.066216227901574
Q1-0.022280043603762
median-0.0029996891591444
mean1.38760937419199e-18
Q30.0175857226156366
maximum0.0635518894806012

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.066216227901574 \tabularnewline
Q1 & -0.022280043603762 \tabularnewline
median & -0.0029996891591444 \tabularnewline
mean & 1.38760937419199e-18 \tabularnewline
Q3 & 0.0175857226156366 \tabularnewline
maximum & 0.0635518894806012 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51700&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]-0.066216227901574[/C][/ROW]
[ROW][C]Q1[/C][C]-0.022280043603762[/C][/ROW]
[ROW][C]median[/C][C]-0.0029996891591444[/C][/ROW]
[ROW][C]mean[/C][C]1.38760937419199e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0175857226156366[/C][/ROW]
[ROW][C]maximum[/C][C]0.0635518894806012[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51700&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51700&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-0.066216227901574
Q1-0.022280043603762
median-0.0029996891591444
mean1.38760937419199e-18
Q30.0175857226156366
maximum0.0635518894806012



Parameters (Session):
par1 = colombia ; par2 = www.ico.org ; par3 = Prices paid to growers in exporting Member countries in US cents per lb (Arabica, 1977/1 - 2006/12) ; par4 = usa ; par5 = www.ico.org ; par6 = Retail prices in importing Member countries in US cents per lb (Arabica, 1977/1 - 2006/12) ;
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')