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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 10:17:09 -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/t1256746669ug59petiamwt1gy.htm/, Retrieved Mon, 06 May 2024 01:24:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51507, Retrieved Mon, 06 May 2024 01:24:44 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS5 bivariate EDA
Estimated Impact79
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [] [2009-10-28 16:17:09] [4563e36d4b7005634fe3557528d9fcab] [Current]
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Dataseries X:
4071
4351
4871
4649
4922
4879
4853
4545
4733
5191
4983
4593
4656
4513
4857
4681
4897
4547
4692
4390
5341
5415
4890
5120
4422
4797
5689
5171
4265
5215
4874
4590
4994
4988
5110
5141
4395
4523
5306
5365
5496
5647
5443
5546
5912
5665
5963
5861
5366
5619
6721
6054
6619
6856
6193
6317
6618
6585
6852
6586
6154
6193
7606
6588
7143
7629
7041
7146
7200
7739
7953
7082
Dataseries Y:
9356
9337
10149
9788
9770
9911
9429
8775
10189
10529
9914
9790
9625
9729
10589
9611
9388
9510
9690
8434
9844
10601
9942
10229
9381
9635
11228
9999
10089
11622
10533
9965
11567
11321
11686
11747
10595
10751
12199
11690
10978
11753
10839
10518
12183
11967
12363
12359
12162
12096
14325
12670
13865
13563
12734
12464
13389
13961
14088
13143
13413
13579
15388
13708
14689
14883
13991
13854
14364
15672
15904
14016




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51507&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]4 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=51507&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51507&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c1438.23645796704
b1.81966826572267

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1438.23645796704 \tabularnewline
b & 1.81966826572267 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51507&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1438.23645796704[/C][/ROW]
[ROW][C]b[/C][C]1.81966826572267[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51507&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51507&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]
c1438.23645796704
b1.81966826572267







Descriptive Statistics about e[t]
# observations72
minimum-1313.08466519183
Q1-413.419859112291
median-9.58671008945868
mean8.17124146124115e-14
Q3330.070904367108
maximum1159.32151418182

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 72 \tabularnewline
minimum & -1313.08466519183 \tabularnewline
Q1 & -413.419859112291 \tabularnewline
median & -9.58671008945868 \tabularnewline
mean & 8.17124146124115e-14 \tabularnewline
Q3 & 330.070904367108 \tabularnewline
maximum & 1159.32151418182 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51507&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]-1313.08466519183[/C][/ROW]
[ROW][C]Q1[/C][C]-413.419859112291[/C][/ROW]
[ROW][C]median[/C][C]-9.58671008945868[/C][/ROW]
[ROW][C]mean[/C][C]8.17124146124115e-14[/C][/ROW]
[ROW][C]Q3[/C][C]330.070904367108[/C][/ROW]
[ROW][C]maximum[/C][C]1159.32151418182[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51507&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51507&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]
# observations72
minimum-1313.08466519183
Q1-413.419859112291
median-9.58671008945868
mean8.17124146124115e-14
Q3330.070904367108
maximum1159.32151418182



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')