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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 computationWed, 28 Oct 2009 12:24:20 -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/t12567543776abjg01syq3e9ry.htm/, Retrieved Sun, 05 May 2024 22:38:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51699, Retrieved Sun, 05 May 2024 22:38:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHW WS 5 - Bivariate EDA ( e[t] en e[t]')
Estimated Impact131

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] [WS 5 - Bivariate ...] [2009-10-28 18:24:20] [a45cc820faa25ce30779915639528ec2] [Current]
- RMP     [Pearson Correlation] [controle correlat...] [2009-11-04 18:50:56] [cd6314e7e707a6546bd4604c9d1f2b69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-2,529152518
-2,982359944
-6,417831562
-1,888774797
-1,400095753
-3,082359944
-3,288774797
-3,535567371
-2,888774797
-0,350850128
-1,975000789
-2,992736598
-0,475000789
-2,510472407
-4,732170017
-0,805566304
-0,61688726
-1,072547738
-1,719340311
-2,490283547
-1,721793363
1,053111673
-0,131605569
-0,731605569
0,437828916
-1,720284613
-2,849341378
1,374809283
-0,213869761
0,982168438
-0,206510606
-0,93707612
-0,654811929
2,414622556
-1,370094686
0,625943512
1,28311274
-1,085377444
-2,290283547
0,991980645
1,267829983
1,474244836
-1,154811929
0,560470828
0,233867115
2,936320167
0,145188071
1,460470828
2,469338733
1,224999211
-0,790283547
1,433867115
3,922546159
2,48462149
-0,333114319
2,68462149
2,816131306
3,140281968
4,607263402
3,111225203
5,587074541
4,264432629
0,208772151
4,58462149
4,297451195
0,090092041
-1,035002923
-1,018211416
-0,414249615
1,018768951
-0,019155718
-0,454627335
1,698580091
Dataseries Y:
Download CSV
Histogram 
-3,713734268
-4,444217543
-6,064539727
-3,405184094
-2,354378635
-3,844217543
-3,105184094
-3,774700819
-3,405184094
-0,840747915
-2,711875557
-3,822036649
-0,611875557
-3,632197741
-3,859211388
-1,64396975
-1,493164292
-1,567761562
-1,237278287
-2,477922654
-1,681392282
0,47610464
-0,957848263
-1,357848263
0,310057544
-2,808653722
-2,168009355
0,303118287
-1,047687171
0,935460273
0,984654814
-0,047439379
-0,35760047
3,210305337
-1,123647567
0,359499878
0,806835708
-1,889694663
-1,277922654
0,411916254
1,040788612
1,201755163
-0,55760047
0,508446626
-0,006795012
2,237318984
-0,05760047
1,508446626
1,813527172
1,088124443
-0,377922654
1,093204988
3,944010447
3,079574268
1,469413177
4,179574268
2,783043897
4,154171539
5,377963351
3,494815906
6,223688264
4,825299181
2,350701911
5,679574268
5,40150737
1,869165384
0,426662306
-0,034552037
-0,417699482
1,058508706
-0,605927472
-1,126249656
1,304233619

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'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=51699&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=51699&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51699&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'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c1.48578006539016e-11
b1.08464130691299

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1.48578006539016e-11 \tabularnewline
b & 1.08464130691299 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51699&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1.48578006539016e-11[/C][/ROW]
[ROW][C]b[/C][C]1.08464130691299[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51699&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51699&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]
c1.48578006539016e-11
b1.08464130691299






Descriptive Statistics about e[t]
# observations73
minimum-1.35654092973246
Q1-0.584881371245165
median-0.164829783669396
mean-5.2600142658557e-17
Q30.479251525235055
maximum2.12425901227747

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 73 \tabularnewline
minimum & -1.35654092973246 \tabularnewline
Q1 & -0.584881371245165 \tabularnewline
median & -0.164829783669396 \tabularnewline
mean & -5.2600142658557e-17 \tabularnewline
Q3 & 0.479251525235055 \tabularnewline
maximum & 2.12425901227747 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51699&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]73[/C][/ROW]
[ROW][C]minimum[/C][C]-1.35654092973246[/C][/ROW]
[ROW][C]Q1[/C][C]-0.584881371245165[/C][/ROW]
[ROW][C]median[/C][C]-0.164829783669396[/C][/ROW]
[ROW][C]mean[/C][C]-5.2600142658557e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.479251525235055[/C][/ROW]
[ROW][C]maximum[/C][C]2.12425901227747[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51699&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51699&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]
# observations73
minimum-1.35654092973246
Q1-0.584881371245165
median-0.164829783669396
mean-5.2600142658557e-17
Q30.479251525235055
maximum2.12425901227747


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')